{
  "capped": false,
  "live": 644,
  "meta": 673,
  "kernels": [
    {
      "ref": "aroy40001/atam-fet-enhanced-ipynb",
      "title": "ATAM FET enhanced.ipynb",
      "source": "live",
      "kernel_id": "131832288"
    },
    {
      "ref": "saida889/atam-fet-notebook2b0707d227",
      "title": "ATAM-FET_notebook2b0707d227",
      "source": "live",
      "kernel_id": "129801524"
    },
    {
      "ref": "hishmaizamy/bias-aware-harmful-content-detection-2541880",
      "title": "Bias-Aware Harmful Content Detection - 2541880",
      "source": "live",
      "kernel_id": "128543933"
    },
    {
      "ref": "nardeenezzzarif/bag-of-words-task",
      "title": "Bag of Words Task",
      "source": "live",
      "kernel_id": "124261496"
    },
    {
      "ref": "mohdhamd/notebookc5460a54cf",
      "title": "notebookc5460a54cf",
      "source": "live",
      "kernel_id": "118087426"
    },
    {
      "ref": "dongtv1302/codetrenghub",
      "title": "CodetrenGhub",
      "source": "live",
      "kernel_id": "117677271"
    },
    {
      "ref": "ducalhp3/notebook2c95d15a32",
      "title": "notebook2c95d15a32",
      "source": "live",
      "kernel_id": "116403807"
    },
    {
      "ref": "sreerammaguluri/notebookc1b636d96f",
      "title": "notebookc1b636d96f",
      "source": "live",
      "kernel_id": "113981577"
    },
    {
      "ref": "vaaven/jigsaw-toxicity-nlp",
      "title": "Jigsaw Toxicity NLP",
      "source": "live",
      "kernel_id": "112002063"
    },
    {
      "ref": "insunghw/jigsaw-gpt2-weighted-submission",
      "title": "jigsaw-gpt2-weighted-submission",
      "source": "live",
      "kernel_id": "103868738"
    },
    {
      "ref": "robifr/notebooke00ba45380",
      "title": "notebooke00ba45380",
      "source": "live",
      "kernel_id": "103865577"
    },
    {
      "ref": "insunghw/jigsaw-gpt2-training",
      "title": "jigsaw-gpt2-training",
      "source": "live",
      "kernel_id": "103427348"
    },
    {
      "ref": "beghouraasma/final-version-pro-2",
      "title": "FINAL_VERSION_Pro-2",
      "source": "live",
      "kernel_id": "101795199"
    },
    {
      "ref": "yasmeenasaad/baseline-for-toxicity-classification",
      "title": "BaseLine for Toxicity Classification",
      "source": "live",
      "kernel_id": "101489130"
    },
    {
      "ref": "gayathrevaidya/open-lab3",
      "title": "Open Lab3",
      "source": "live",
      "kernel_id": "92263575"
    },
    {
      "ref": "hugomojicaangarita/datatoxicity",
      "title": "DataToxicity",
      "source": "live",
      "kernel_id": "86900383"
    },
    {
      "ref": "huxuebing/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "83765845"
    },
    {
      "ref": "pengyili29/single-lstm-fan-xuanping-spbu",
      "title": "Single LSTM_Fan Xuanping_SPBU",
      "source": "live",
      "kernel_id": "81853270"
    },
    {
      "ref": "minihihihaha/jigsaw-bert-tftransformers-baseline",
      "title": "Jigsaw_BERT(TFtransformers)_baseline",
      "source": "live",
      "kernel_id": "73449924"
    },
    {
      "ref": "irdeal/tfrecord-data-generation",
      "title": "TFRecord Data generation",
      "source": "live",
      "kernel_id": "61289489"
    },
    {
      "ref": "hmmhmmh/jigsaw-2nd",
      "title": "jigsaw_2nd",
      "source": "live",
      "kernel_id": "61218608"
    },
    {
      "ref": "mvvppp/l9-m3",
      "title": "L9_M3",
      "source": "live",
      "kernel_id": "61190111"
    },
    {
      "ref": "hmmhmmh/jigsaw-dataset",
      "title": "jigsaw dataset",
      "source": "live",
      "kernel_id": "61124624"
    },
    {
      "ref": "mahmoudelkarargy/toxiccommentclassification",
      "title": "ToxicCommentClassification",
      "source": "live",
      "kernel_id": "58590849"
    },
    {
      "ref": "cooperkaggle/unintended-bias-in-toxicity-classification",
      "title": "Unintended Bias in Toxicity Classification",
      "source": "live",
      "kernel_id": "57145907"
    },
    {
      "ref": "hk3820/jigsaw-bert-inference-dsga1017",
      "title": "Jigsaw BERT Inference - DSGA1017",
      "source": "live",
      "kernel_id": "54459978"
    },
    {
      "ref": "dhruvjoshi892/submitt",
      "title": "submitt",
      "source": "live",
      "kernel_id": "47811399"
    },
    {
      "ref": "dhruvjoshi892/sajud-research-1",
      "title": "sajud_research_1",
      "source": "live",
      "kernel_id": "47281400"
    },
    {
      "ref": "metehanpolat1705/toxicdata",
      "title": "toxicData",
      "source": "live",
      "kernel_id": "40660354"
    },
    {
      "ref": "suraj520/longformer-know-train-infer",
      "title": "[Longformer]Know📚, Train⚙️ & Infer🧐",
      "source": "live",
      "kernel_id": "40268937"
    },
    {
      "ref": "maksaiza/main-model",
      "title": "Main_model",
      "source": "live",
      "kernel_id": "40244331"
    },
    {
      "ref": "gpreda/jigsaw-simple-baseline",
      "title": "Jigsaw Simple Baseline",
      "source": "live",
      "kernel_id": "40134269"
    },
    {
      "ref": "cthulhucoder/simple-lstm-pytorch-version",
      "title": "Simple LSTM Pytorch version",
      "source": "live",
      "kernel_id": "40030723"
    },
    {
      "ref": "cthulhucoder/simple-lstm-gensim",
      "title": "Simple LSTM Gensim",
      "source": "live",
      "kernel_id": "39941786"
    },
    {
      "ref": "gpreda/jigsaw-comments-text-exploration",
      "title": "Jigsaw Comments Text Exploration",
      "source": "live",
      "kernel_id": "39607412"
    },
    {
      "ref": "gpreda/jigsaw-predict-bert-large",
      "title": "Jigsaw_predict_BERT_large",
      "source": "live",
      "kernel_id": "39564469"
    },
    {
      "ref": "gpreda/jigsaw-predict-bert-small",
      "title": "Jigsaw_predict_BERT_small",
      "source": "live",
      "kernel_id": "39563418"
    },
    {
      "ref": "yahiamohamed/toxicity-classification",
      "title": "Toxicity Classification",
      "source": "live",
      "kernel_id": "37382624"
    },
    {
      "ref": "mikhillal/toxic-comment-classification-lr-cnn-lstm",
      "title": "Toxic Comment Classification(LR+CNN+LSTM)",
      "source": "live",
      "kernel_id": "36938480"
    },
    {
      "ref": "aceofspades4171/kaggle-project",
      "title": "Kaggle_Project",
      "source": "live",
      "kernel_id": "36250703"
    },
    {
      "ref": "anantpandey29/jubtc-complete-classification-approach",
      "title": "JUBTC - Complete Classification Approach",
      "source": "live",
      "kernel_id": "36012398"
    },
    {
      "ref": "kiraigo/simple-lstm-pytorch-version",
      "title": "Simple LSTM - PyTorch version",
      "source": "live",
      "kernel_id": "33643420"
    },
    {
      "ref": "micheldc55/tutorial-eda-for-nlp-how-to-build-a-vocabulary",
      "title": "tutorial EDA for NLP & how to build a vocabulary",
      "source": "live",
      "kernel_id": "33423042"
    },
    {
      "ref": "trngtrunghiu/519h0107-519h0164-so-7-bai-2-lr",
      "title": "519H0107 - 519H0164 - So 7 - Bai 2_LR",
      "source": "live",
      "kernel_id": "33270643"
    },
    {
      "ref": "trngtrunghiu/519h0107-519h0164-so-7-bai-2-rnn",
      "title": "519H0107 - 519H0164 - So 7 - Bai 2_RNN",
      "source": "live",
      "kernel_id": "33267158"
    },
    {
      "ref": "gazu468/all-about-bert-you-need-to-know",
      "title": "All about Bert you need to know",
      "source": "live",
      "kernel_id": "32665951"
    },
    {
      "ref": "matthewmazzaccaro/notebook4629e521b3",
      "title": "notebook4629e521b3",
      "source": "live",
      "kernel_id": "32449317"
    },
    {
      "ref": "fulrose/fkms-preprocessing",
      "title": "[FKMs] Preprocessing",
      "source": "live",
      "kernel_id": "32256359"
    },
    {
      "ref": "vinay2003/notebook9a821cb9a5",
      "title": "notebook9a821cb9a5",
      "source": "live",
      "kernel_id": "31565709"
    },
    {
      "ref": "jarvis11/toxic-comment-classification-with-tuning",
      "title": "Toxic Comment Classification with tuning",
      "source": "live",
      "kernel_id": "30197352"
    },
    {
      "ref": "abdalrahmanshahrour/toxic-text-classification",
      "title": "Toxic Text Classification",
      "source": "live",
      "kernel_id": "29615608"
    },
    {
      "ref": "mohammadaflahkhan/dataset-processing-for-targets",
      "title": "Dataset Processing for Targets",
      "source": "live",
      "kernel_id": "29548995"
    },
    {
      "ref": "omarkhald/06-use-transformer-and-simple-nn",
      "title": " 06- use transformer and simple NN",
      "source": "live",
      "kernel_id": "27603399"
    },
    {
      "ref": "omarkhald/05-word-embeddings-lstm",
      "title": "05- word Embeddings & LSTM",
      "source": "live",
      "kernel_id": "27550796"
    },
    {
      "ref": "omarkhald/04-word-embeddings-ngrams-using-cnn",
      "title": "04- word Embeddings & ngrams using cnn",
      "source": "live",
      "kernel_id": "27545614"
    },
    {
      "ref": "omarkhald/03-simple-word-embeddings-solution",
      "title": "03- simple word Embeddings solution",
      "source": "live",
      "kernel_id": "27516442"
    },
    {
      "ref": "omarkhald/02-classic-nlp-solution",
      "title": "02-classic nlp solution",
      "source": "live",
      "kernel_id": "27511727"
    },
    {
      "ref": "omarkhald/01-classic-nlp-solution",
      "title": "01-classic nlp solution",
      "source": "live",
      "kernel_id": "27509413"
    },
    {
      "ref": "youin10uosai/wombat-inference-kernel",
      "title": "Wombat Inference Kernel",
      "source": "live",
      "kernel_id": "26653658"
    },
    {
      "ref": "minhazreza/target-community-identification",
      "title": "Target Community Identification",
      "source": "live",
      "kernel_id": "26148870"
    },
    {
      "ref": "viethoang97/sc203",
      "title": "sc203",
      "source": "live",
      "kernel_id": "25448872"
    },
    {
      "ref": "lipech123/harmful-bias-data",
      "title": "Harmful bias data",
      "source": "live",
      "kernel_id": "24655084"
    },
    {
      "ref": "kaerunantoka/jigsaw4-create-additional-pair-w-jigsaw1",
      "title": "Jigsaw4 : create additional pair w/ jigsaw1",
      "source": "live",
      "kernel_id": "24449779"
    },
    {
      "ref": "dhainiksuthar/toxic-comment-classification",
      "title": "Toxic comment classification",
      "source": "live",
      "kernel_id": "24449449"
    },
    {
      "ref": "coreacasa/jigsaw4-luke-large-training-tito-cv-strategy",
      "title": "Jigsaw4-Luke-large-Training-Tito-CV-strategy",
      "source": "live",
      "kernel_id": "24434176"
    },
    {
      "ref": "coreacasa/jigsaw4-luke-base-training-tito-cv-strategy",
      "title": "Jigsaw4-Luke-base-Training-Tito-CV-strategy",
      "source": "live",
      "kernel_id": "24433726"
    },
    {
      "ref": "dhainiksuthar/toxic-comment",
      "title": "toxic comment",
      "source": "live",
      "kernel_id": "24406367"
    },
    {
      "ref": "ilosvigil/jigsaw-train-debertav3-pytorch-lightning",
      "title": "Jigsaw - Train DeBERTaV3 (PyTorch Lightning)",
      "source": "live",
      "kernel_id": "24381771"
    },
    {
      "ref": "kaerunantoka/jigsaw4-previous-data-preprocessing",
      "title": "Jigsaw4 : Previous Data Preprocessing",
      "source": "live",
      "kernel_id": "23944044"
    },
    {
      "ref": "athirakaladharan/toxic-comment-classification-logreg-distilbert",
      "title": "Toxic_Comment_Classification_LogReg_DistilBERT",
      "source": "live",
      "kernel_id": "23910880"
    },
    {
      "ref": "shravankumar147/2-toxic-comment-data-preperation",
      "title": "2. Toxic Comment Data Preperation",
      "source": "live",
      "kernel_id": "23878289"
    },
    {
      "ref": "hidebu/luke-base-add-datasets-private-0-8011",
      "title": "Luke-base, add datasets (Private:0.8011)",
      "source": "live",
      "kernel_id": "23820401"
    },
    {
      "ref": "preethgunasekaran/toxicity-eda-preprocessing",
      "title": "Toxicity EDA & Preprocessing",
      "source": "live",
      "kernel_id": "23801609"
    },
    {
      "ref": "huntergregory/ranking-toxicity-of-wikipedia-comments-eda",
      "title": "Ranking Toxicity of Wikipedia Comments - EDA",
      "source": "live",
      "kernel_id": "23780414"
    },
    {
      "ref": "zsofislosar/toxicity-data-prep",
      "title": "Toxicity  data prep",
      "source": "live",
      "kernel_id": "23775521"
    },
    {
      "ref": "dooneen/notebook585d78e2db",
      "title": "notebook585d78e2db",
      "source": "live",
      "kernel_id": "22772910"
    },
    {
      "ref": "vspiral/notebook13528d02fb",
      "title": "notebook13528d02fb",
      "source": "live",
      "kernel_id": "22758948"
    },
    {
      "ref": "yifanmikeyu/simple-gru-bert",
      "title": "Simple GRU + BERT",
      "source": "live",
      "kernel_id": "22599982"
    },
    {
      "ref": "yifanmikeyu/notebook513ea1233b",
      "title": "notebook513ea1233b",
      "source": "live",
      "kernel_id": "22568665"
    },
    {
      "ref": "masatomurakawamm/jigsaw-bert-tftransformers-baseline",
      "title": "Jigsaw_BERT(TFtransformers)_baseline",
      "source": "live",
      "kernel_id": "22502790"
    },
    {
      "ref": "adldotori/all-in-one-dataset",
      "title": "All-in-One Dataset",
      "source": "live",
      "kernel_id": "22457529"
    },
    {
      "ref": "seraphwedd18/jigsaw-toxic-severity-word-usage-scoring",
      "title": "Jigsaw Toxic Severity - Word Usage Scoring",
      "source": "live",
      "kernel_id": "22226359"
    },
    {
      "ref": "seraphwedd18/jigsaw-toxic-severity-lightgbm-training",
      "title": "Jigsaw Toxic Severity - LightGBM Training",
      "source": "live",
      "kernel_id": "22098766"
    },
    {
      "ref": "gauravbrills/jigsaw-luke-train-with-torch-xla",
      "title": "Jigsaw Luke [train] with torch_xla",
      "source": "live",
      "kernel_id": "22093864"
    },
    {
      "ref": "yasufuminakama/jigsaw4-luke-base-starter-train",
      "title": "Jigsaw4 / Luke-base / starter [train]",
      "source": "live",
      "kernel_id": "22071684"
    },
    {
      "ref": "je0102/toxic-comment-detection-30e44f",
      "title": "Toxic Comment Detection 30e44f",
      "source": "live",
      "kernel_id": "22008534"
    },
    {
      "ref": "minhazreza/toxicity-detection-with-four-preliminary-models",
      "title": "Toxicity Detection with Four Preliminary Models",
      "source": "live",
      "kernel_id": "21996023"
    },
    {
      "ref": "junior10/j-toxicity-code",
      "title": "J_Toxicity_code",
      "source": "live",
      "kernel_id": "21870579"
    },
    {
      "ref": "minhazreza/toxicity-classification-gru-lstm",
      "title": "Toxicity Classification - GRU, LSTM",
      "source": "live",
      "kernel_id": "21674612"
    },
    {
      "ref": "sandynigs/ensemble-models-jigsaw",
      "title": "Ensemble Models Jigsaw",
      "source": "live",
      "kernel_id": "21111009"
    },
    {
      "ref": "sandynigs/jigsaw-bidirectional-gru-model",
      "title": "Jigsaw BiDirectional GRU Model",
      "source": "live",
      "kernel_id": "21025880"
    },
    {
      "ref": "sandynigs/jigsaw-cnn-model",
      "title": "Jigsaw CNN Model",
      "source": "live",
      "kernel_id": "20990555"
    },
    {
      "ref": "gayatriilan/xlnet-finetuning-tensorflow",
      "title": "XLNet FineTuning - TensorFlow",
      "source": "live",
      "kernel_id": "18953137"
    },
    {
      "ref": "ameythakur20/exercise-identifying-bias-in-ai",
      "title": "Exercise: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "18761640"
    },
    {
      "ref": "fulrose/ds-0722-problem-02",
      "title": "[DS_0722] Problem_02",
      "source": "live",
      "kernel_id": "18744709"
    },
    {
      "ref": "vishweshsalodkar/jigsaw",
      "title": "JIGSAW",
      "source": "live",
      "kernel_id": "18505797"
    },
    {
      "ref": "raisulju/jigsaw-unintended-bias-eda-preprocessing",
      "title": "Jigsaw Unintended Bias EDA & Preprocessing",
      "source": "live",
      "kernel_id": "18125405"
    },
    {
      "ref": "shohrabhossenniaz/toxicity-classification",
      "title": "Toxicity Classification",
      "source": "live",
      "kernel_id": "18120784"
    },
    {
      "ref": "homiarafarhana/jigsaw-sgd",
      "title": "Jigsaw_SGD",
      "source": "live",
      "kernel_id": "18052993"
    },
    {
      "ref": "homiarafarhana/jigsaw-cnn",
      "title": "Jigsaw_CNN",
      "source": "live",
      "kernel_id": "18052393"
    },
    {
      "ref": "homiarafarhana/jigsaw-lstm",
      "title": "Jigsaw_LSTM",
      "source": "live",
      "kernel_id": "18052343"
    },
    {
      "ref": "afrinjubaida/toxicity",
      "title": "Toxicity",
      "source": "live",
      "kernel_id": "18051586"
    },
    {
      "ref": "homiarafarhana/identifying-bias-and-possible-reason",
      "title": "Identifying Bias and possible reason",
      "source": "live",
      "kernel_id": "18050805"
    },
    {
      "ref": "fahimmahmood/bert-submission",
      "title": "Bert Submission",
      "source": "live",
      "kernel_id": "18016639"
    },
    {
      "ref": "fahimmahmood/rnn-lstm",
      "title": "RNN(LSTM)",
      "source": "live",
      "kernel_id": "17979551"
    },
    {
      "ref": "makatronium/toxicity-detection-and-minimizing-bias",
      "title": "Toxicity Detection and Minimizing Bias",
      "source": "live",
      "kernel_id": "17914152"
    },
    {
      "ref": "rajeshsundaram/exercise-identifying-bias-in-ai",
      "title": "Exercise: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "17858977"
    },
    {
      "ref": "fahimmahmood/jigsaw-toxic-comment-detection",
      "title": "Jigsaw Toxic Comment Detection",
      "source": "live",
      "kernel_id": "17850916"
    },
    {
      "ref": "mohamedtaha7/toxicity-from-text-gru-lstm",
      "title": "Toxicity from Text - GRU, LSTM",
      "source": "live",
      "kernel_id": "17016373"
    },
    {
      "ref": "moemenalaa97/assignment7",
      "title": "Assignment7",
      "source": "live",
      "kernel_id": "17014139"
    },
    {
      "ref": "amiraabdelalim/notebook87071737e8",
      "title": "notebook87071737e8",
      "source": "live",
      "kernel_id": "17011834"
    },
    {
      "ref": "spotbox/exercise-identifying-bias-in-ai",
      "title": "Exercise: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "17004620"
    },
    {
      "ref": "faridsharaf/jigwas-toxic-classification",
      "title": "Jigwas Toxic Classification",
      "source": "live",
      "kernel_id": "16999427"
    },
    {
      "ref": "abdokamr/starter-eda-baseline-tf-idf-lr",
      "title": "Starter EDA + Baseline(TF-IDF + LR)",
      "source": "live",
      "kernel_id": "16975920"
    },
    {
      "ref": "vijendersingh412/the-effect-use-of-word-embeddings",
      "title": "The Effect use of Word Embeddings",
      "source": "live",
      "kernel_id": "16718972"
    },
    {
      "ref": "dennisho/exercise-identifying-bias-in-ai",
      "title": "Exercise: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "16360063"
    },
    {
      "ref": "swetko/cse416-identifying-bias-in-ai",
      "title": "CSE416: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "16359680"
    },
    {
      "ref": "georgezoto/intro-to-ai-ethics-identifying-bias-in-ai",
      "title": "Intro to AI Ethics - Identifying Bias in AI",
      "source": "live",
      "kernel_id": "16335794"
    },
    {
      "ref": "hsinwenchang/kaggle-bipoc-grant-talk",
      "title": "Kaggle BIPOC Grant Talk",
      "source": "live",
      "kernel_id": "16170342"
    },
    {
      "ref": "naim99/toxic-bert-plain-vanila",
      "title": "Toxic  BERT plain vanila",
      "source": "live",
      "kernel_id": "16158178"
    },
    {
      "ref": "tsarikamurty2037059/exercise-identifying-bias-in-ai",
      "title": "Exercise: Identifying Bias in AI",
      "source": "live",
      "kernel_id": "16109447"
    },
    {
      "ref": "prabhnoor0212/bert-pre-train",
      "title": "Bert pre train",
      "source": "live",
      "kernel_id": "15126540"
    },
    {
      "ref": "mayukhdutta/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "14887075"
    },
    {
      "ref": "amrutiashivani/nlp-toxicity-classification",
      "title": "NLP Toxicity Classification",
      "source": "live",
      "kernel_id": "14302930"
    },
    {
      "ref": "kasmithh/unintended-bias-in-toxicity-data-view",
      "title": "Unintended Bias in Toxicity Data View",
      "source": "live",
      "kernel_id": "14060493"
    },
    {
      "ref": "naim99/tunizi-using-bert-embeddings",
      "title": "tunizi [using BERT embeddings]",
      "source": "live",
      "kernel_id": "13947892"
    },
    {
      "ref": "emmamichael101/toxicity-bias-logistic-regression-tfidfvectorizer",
      "title": "Toxicity Bias Logistic Regression, TfidfVectorizer",
      "source": "live",
      "kernel_id": "13877116"
    },
    {
      "ref": "realdeo/notebook518e81e276",
      "title": "notebook518e81e276",
      "source": "live",
      "kernel_id": "12774496"
    },
    {
      "ref": "fulrose/kakr-4th-seminar-feature-engineering",
      "title": "[KaKr 4th seminar] Feature Engineering ",
      "source": "live",
      "kernel_id": "12608004"
    },
    {
      "ref": "muhammadrehan444/toxicity-classification-step-by-step",
      "title": "Toxicity Classification: Step by Step ",
      "source": "live",
      "kernel_id": "12503055"
    },
    {
      "ref": "kagglebrun/lstm-using-glove",
      "title": "LSTM Using GloVe",
      "source": "live",
      "kernel_id": "12110639"
    },
    {
      "ref": "fredericods/cpe882-feature-based-model-2-gram",
      "title": "[CPE882] Feature-based model (2-gram)",
      "source": "live",
      "kernel_id": "11446659"
    },
    {
      "ref": "reyadmorshed/toxic-bert-plain-vanila",
      "title": "Toxic  BERT plain vanila",
      "source": "live",
      "kernel_id": "11436100"
    },
    {
      "ref": "fredericods/cpe882-feature-based-model-1-gram",
      "title": "[CPE882] Feature-based model (1-gram)",
      "source": "live",
      "kernel_id": "11408394"
    },
    {
      "ref": "fulrose/fkms-inference",
      "title": "[FKMs] Inference",
      "source": "live",
      "kernel_id": "10932780"
    },
    {
      "ref": "shubham10i/toxicity-classification-using-rnn",
      "title": "Toxicity Classification using RNN",
      "source": "live",
      "kernel_id": "10796434"
    },
    {
      "ref": "omarkhald/toxicity-classification-ipynb",
      "title": "Toxicity Classification.ipynb",
      "source": "live",
      "kernel_id": "10781102"
    },
    {
      "ref": "saitakli/basic-biderectional-lstm-jigsaw",
      "title": "Basic Biderectional LSTM Jigsaw",
      "source": "live",
      "kernel_id": "10608865"
    },
    {
      "ref": "fatmaelzhraa/toxicity-classification",
      "title": "Toxicity Classification",
      "source": "live",
      "kernel_id": "10587779"
    },
    {
      "ref": "glorythesky/submit-test",
      "title": "submit_test",
      "source": "live",
      "kernel_id": "10515619"
    },
    {
      "ref": "erikhou/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "9980523"
    },
    {
      "ref": "tozzig/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "9980013"
    },
    {
      "ref": "buntyshah/jigsaw-classification-lstm-content-moderation",
      "title": "Jigsaw Classification LSTM Content Moderation",
      "source": "live",
      "kernel_id": "9415213"
    },
    {
      "ref": "ankushjain2001/the-effect-of-word-embeddings-on-bias",
      "title": "The Effect of Word Embeddings on Bias",
      "source": "live",
      "kernel_id": "9381763"
    },
    {
      "ref": "mittamaria/toxic-comments-pytorch-lstm",
      "title": "Toxic comments - PyTorch LSTM",
      "source": "live",
      "kernel_id": "8959972"
    },
    {
      "ref": "fulrose/fkms-data-generation",
      "title": "[FKMs] Data generation",
      "source": "live",
      "kernel_id": "8801527"
    },
    {
      "ref": "dergel/jigsaw-toxicity-lstm-big-bert",
      "title": "Jigsaw Toxicity: LSTM+BIG_BERT",
      "source": "live",
      "kernel_id": "8777002"
    },
    {
      "ref": "fulrose/fkms-bert-training",
      "title": "[FKMs] Bert training",
      "source": "live",
      "kernel_id": "8762583"
    },
    {
      "ref": "fulrose/fkms-eda",
      "title": "[FKMs] EDA",
      "source": "live",
      "kernel_id": "8735034"
    },
    {
      "ref": "reukki/lstm-study",
      "title": "LSTM study",
      "source": "live",
      "kernel_id": "8681892"
    },
    {
      "ref": "ahoo1260/ocr-post-correction-using-nlp-bert",
      "title": "OCR post correction using NLP BERT",
      "source": "live",
      "kernel_id": "8506912"
    },
    {
      "ref": "jtdsouza/bert-inference-jds",
      "title": "BERT Inference-JDS",
      "source": "live",
      "kernel_id": "7882517"
    },
    {
      "ref": "mingolovestime/kernel276501e036",
      "title": "kernel276501e036",
      "source": "live",
      "kernel_id": "7862756"
    },
    {
      "ref": "doomdiskday/fulltutorial-from-eda-to-ensembles-all-you-need",
      "title": "[FullTutorial] From EDA to Ensembles, all you need",
      "source": "live",
      "kernel_id": "7660456"
    },
    {
      "ref": "hostil/jigsaw-2019-generalized-linear-model-on-bigrams",
      "title": "Jigsaw 2019: Generalized linear model on bigrams",
      "source": "live",
      "kernel_id": "7583758"
    },
    {
      "ref": "mojtylor/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "7493069"
    },
    {
      "ref": "saitakli/lstm-working",
      "title": "LSTM working",
      "source": "live",
      "kernel_id": "7483439"
    },
    {
      "ref": "bparesh/cnn-5fold",
      "title": "cnn-5fold",
      "source": "live",
      "kernel_id": "7340457"
    },
    {
      "ref": "bparesh/bilstm-jigsaw",
      "title": "bilstm-jigsaw",
      "source": "live",
      "kernel_id": "7321883"
    },
    {
      "ref": "sorenj/toxictransitions",
      "title": "ToxicTransitions",
      "source": "live",
      "kernel_id": "7290475"
    },
    {
      "ref": "singhaditya5842/stacked-model",
      "title": "Stacked Model ",
      "source": "live",
      "kernel_id": "7161791"
    },
    {
      "ref": "singhaditya5842/with-gbdt-model",
      "title": "With GBDT Model",
      "source": "live",
      "kernel_id": "7061520"
    },
    {
      "ref": "jmourad100/toxicity-detection-using-bert-embeddings",
      "title": "Toxicity Detection [using BERT embeddings]",
      "source": "live",
      "kernel_id": "6934804"
    },
    {
      "ref": "patricia92fa/jigsaw-competition-part-i-exploratory-analysis",
      "title": "Jigsaw Competition Part I - Exploratory Analysis",
      "source": "live",
      "kernel_id": "6926943"
    },
    {
      "ref": "jasmeetkaur/jigsaw-toxic-classification-with-lstm-attention",
      "title": "Jigsaw Toxic Classification With LSTM Attention ",
      "source": "live",
      "kernel_id": "6926299"
    },
    {
      "ref": "johnlau/jigsaw-convulotional-lstm",
      "title": "Jigsaw - convulotional LSTM",
      "source": "live",
      "kernel_id": "6850926"
    },
    {
      "ref": "irvingzqy/kernel66d2937e6e",
      "title": "kernel66d2937e6e",
      "source": "live",
      "kernel_id": "6840715"
    },
    {
      "ref": "bparesh/jigsaw-nbsvm",
      "title": "jigsaw-nbsvm",
      "source": "live",
      "kernel_id": "6825224"
    },
    {
      "ref": "skilleen/machine-learning-lab-iwd",
      "title": "Machine Learning Lab IWD",
      "source": "live",
      "kernel_id": "6809172"
    },
    {
      "ref": "bhuvan93/simple-lstm-pytorch-version",
      "title": "Simple LSTM - PyTorch version",
      "source": "live",
      "kernel_id": "6801713"
    },
    {
      "ref": "irvingzqy/simple-lstm-c47b65",
      "title": "Simple LSTM c47b65",
      "source": "live",
      "kernel_id": "6796134"
    },
    {
      "ref": "karan100194/kernel7c52d4d57a",
      "title": "kernel7c52d4d57a",
      "source": "live",
      "kernel_id": "6741493"
    },
    {
      "ref": "saranyashalya/pytorch-bert-sequence-classification",
      "title": "Pytorch BERT- Sequence Classification",
      "source": "live",
      "kernel_id": "6677599"
    },
    {
      "ref": "sishihara/translate-en-ja",
      "title": "translate en -> ja",
      "source": "live",
      "kernel_id": "6642728"
    },
    {
      "ref": "austvan/research",
      "title": "Research",
      "source": "live",
      "kernel_id": "6408318"
    },
    {
      "ref": "usgzjzj17273/kernel194010926a",
      "title": "kernel194010926a",
      "source": "live",
      "kernel_id": "6402593"
    },
    {
      "ref": "twrobel/lab-draft",
      "title": "Lab draft",
      "source": "live",
      "kernel_id": "6390044"
    },
    {
      "ref": "twrobel/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "6389214"
    },
    {
      "ref": "cjinny/bert-eda",
      "title": "Bert EDA",
      "source": "live",
      "kernel_id": "6268620"
    },
    {
      "ref": "jedemdasseine/tinkoff-bert",
      "title": "Tinkoff BERT",
      "source": "live",
      "kernel_id": "6130888"
    },
    {
      "ref": "eskender/bert-lstm-rank-blender-4edc9f",
      "title": "BERT + LSTM (rank blender) 4edc9f",
      "source": "live",
      "kernel_id": "6118380"
    },
    {
      "ref": "eskender/tin-part-1",
      "title": "Tin Part 1",
      "source": "live",
      "kernel_id": "6109830"
    },
    {
      "ref": "khyeh0719/kaggle-days-workshop-toxic-bert",
      "title": "Kaggle Days Workshop- Toxic BERT",
      "source": "live",
      "kernel_id": "6041596"
    },
    {
      "ref": "testaccount93/mypersonality",
      "title": "mypersonality",
      "source": "live",
      "kernel_id": "6022815"
    },
    {
      "ref": "felipemello/jigsaw",
      "title": "jigsaw",
      "source": "live",
      "kernel_id": "6022580"
    },
    {
      "ref": "sanilsingh/kernelfda3a6d278",
      "title": "kernelfda3a6d278",
      "source": "live",
      "kernel_id": "5999284"
    },
    {
      "ref": "mastreips/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "5981727"
    },
    {
      "ref": "souravdas4/jigsaw-unintended-bias-in-toxicity-classification",
      "title": "Jigsaw Unintended Bias in Toxicity Classification",
      "source": "live",
      "kernel_id": "5979479"
    },
    {
      "ref": "harendrap/fastai-ulmfit-tutorial",
      "title": "fastai ulmfit tutorial",
      "source": "live",
      "kernel_id": "5882261"
    },
    {
      "ref": "charan977/kernel7b611e177b",
      "title": "kernel7b611e177b",
      "source": "live",
      "kernel_id": "5798046"
    },
    {
      "ref": "charan977/kernel1b4bc2091a",
      "title": "kernel1b4bc2091a",
      "source": "live",
      "kernel_id": "5792677"
    },
    {
      "ref": "charan977/kernel20c4cd278d",
      "title": "kernel20c4cd278d",
      "source": "live",
      "kernel_id": "5792038"
    },
    {
      "ref": "charan977/kernel3acf2f2a3f",
      "title": "kernel3acf2f2a3f",
      "source": "live",
      "kernel_id": "5791352"
    },
    {
      "ref": "charan977/kernele23e0ff4f8",
      "title": "kernele23e0ff4f8",
      "source": "live",
      "kernel_id": "5790632"
    },
    {
      "ref": "austvan/data-exploration",
      "title": "Data Exploration",
      "source": "live",
      "kernel_id": "5785598"
    },
    {
      "ref": "nikkisharma/spacy-explored-toxic-texts",
      "title": "spaCY explored Toxic Texts !!!",
      "source": "live",
      "kernel_id": "5704797"
    },
    {
      "ref": "sonali0103/kernel5f6932067d",
      "title": "kernel5f6932067d",
      "source": "live",
      "kernel_id": "5704368"
    },
    {
      "ref": "sid321axn/spacy-explored-toxic-texts",
      "title": "spaCY explored Toxic Texts !!!",
      "source": "live",
      "kernel_id": "5688923"
    },
    {
      "ref": "heshamasem/toxic-text-classification",
      "title": "Toxic Text Classification",
      "source": "live",
      "kernel_id": "5641528"
    },
    {
      "ref": "ilyamironov/jigsaw-toxicity-classification-lstm-v4",
      "title": "Jigsaw_Toxicity_Classification_LSTM_v4",
      "source": "live",
      "kernel_id": "5617375"
    },
    {
      "ref": "s8a496b/char-model-test",
      "title": "char_model_test",
      "source": "live",
      "kernel_id": "5612390"
    },
    {
      "ref": "nihal24/toxicity-with-simple-single-gru-layer",
      "title": "Toxicity with Simple Single GRU Layer",
      "source": "live",
      "kernel_id": "5471882"
    },
    {
      "ref": "sorenj/contextmatters",
      "title": "ContextMatters",
      "source": "live",
      "kernel_id": "5373311"
    },
    {
      "ref": "takumiito/bertimplements",
      "title": "bertImplements",
      "source": "live",
      "kernel_id": "5265537"
    },
    {
      "ref": "xooca1/bert-sentiment-analysis-pytorch",
      "title": "bert_sentiment_analysis_pytorch",
      "source": "live",
      "kernel_id": "5252991"
    },
    {
      "ref": "curiousprogrammer/xlnet-finetuning-tensorflow",
      "title": "XLNet FineTuning - TensorFlow",
      "source": "live",
      "kernel_id": "5085637"
    },
    {
      "ref": "curiousprogrammer/xlnet-with-imdb-classifier-base-model",
      "title": "XLNet - With IMDB Classifier - Base Model",
      "source": "live",
      "kernel_id": "5073162"
    },
    {
      "ref": "kalashnimov/attention-with-fold",
      "title": "Attention with Fold",
      "source": "live",
      "kernel_id": "5030121"
    },
    {
      "ref": "pochineni/prediction-submission-glove",
      "title": "Prediction Submission_GloVe",
      "source": "live",
      "kernel_id": "5012912"
    },
    {
      "ref": "shivangchopra11/save-bert-fine-tuning-model",
      "title": "Save BERT fine-tuning model",
      "source": "live",
      "kernel_id": "5009390"
    },
    {
      "ref": "gsailalitha/kerneld019288abf",
      "title": "kerneld019288abf",
      "source": "live",
      "kernel_id": "5006981"
    },
    {
      "ref": "httpwwwfszyc/keras-models-inference",
      "title": "keras Models inference",
      "source": "live",
      "kernel_id": "4958771"
    },
    {
      "ref": "shushanxingzhe/bert-a-fine-tuning-example",
      "title": "BERT: a fine tuning example",
      "source": "live",
      "kernel_id": "4951567"
    },
    {
      "ref": "pochineni/feature-engineering",
      "title": "Feature Engineering",
      "source": "live",
      "kernel_id": "4934895"
    },
    {
      "ref": "ceshine/toxic-2019-simple-ensemble-public",
      "title": "Toxic 2019 Simple Ensemble (Public)",
      "source": "live",
      "kernel_id": "4919013"
    },
    {
      "ref": "pochineni/base-model-lstm-model-without-pretrained-embedding",
      "title": "Base Model LSTM Model without Pretrained Embedding",
      "source": "live",
      "kernel_id": "4915706"
    },
    {
      "ref": "ceshine/bert-finetuning-public",
      "title": " Bert Finetuning (Public)",
      "source": "live",
      "kernel_id": "4905499"
    },
    {
      "ref": "zhangmw/toxic-bert-plain-vanila",
      "title": "Toxic  BERT plain vanila",
      "source": "live",
      "kernel_id": "4892695"
    },
    {
      "ref": "gauripradhan/toxicity-detection-using-bert-embeddings",
      "title": "Toxicity Detection [using BERT embeddings]",
      "source": "live",
      "kernel_id": "4890138"
    },
    {
      "ref": "kenil020/sentiment-analysis-for-toxicity-in-a-statement",
      "title": "Sentiment Analysis for Toxicity in a Statement",
      "source": "live",
      "kernel_id": "4881289"
    },
    {
      "ref": "sriharipramod/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "4846210"
    },
    {
      "ref": "takumiito/commented-bert-a-fine-tuning-example",
      "title": "Commented_BERT: a fine tuning example",
      "source": "live",
      "kernel_id": "4839565"
    },
    {
      "ref": "yuooka/jigsaw-bert-demo-190719",
      "title": "Jigsaw_BERT_demo_190719",
      "source": "live",
      "kernel_id": "4817754"
    },
    {
      "ref": "animeshsinha1309/simple-lstm-for-toxicity-classification",
      "title": "Simple LSTM for Toxicity Classification",
      "source": "live",
      "kernel_id": "4797386"
    },
    {
      "ref": "yosefardhito/pytorch-lstm-end-to-end-walkthrough",
      "title": "PyTorch LSTM End-to-end Walkthrough",
      "source": "live",
      "kernel_id": "4791572"
    },
    {
      "ref": "payert/jigsaw-model-comparison",
      "title": "Jigsaw_Model_comparison",
      "source": "live",
      "kernel_id": "4785164"
    },
    {
      "ref": "mayvid/jigsaw",
      "title": "jigsaw",
      "source": "live",
      "kernel_id": "4770060"
    },
    {
      "ref": "vaibhavmathur96/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "4760372"
    },
    {
      "ref": "andyandy/text-classification-lstm-glove-vector",
      "title": "Text Classification. LSTM+Glove Vector ",
      "source": "live",
      "kernel_id": "4737266"
    },
    {
      "ref": "pappukrjha/know-your-data",
      "title": "know your data",
      "source": "live",
      "kernel_id": "4687356"
    },
    {
      "ref": "tomohiro05/polyglot-and-sklearn",
      "title": "polyglot and sklearn",
      "source": "live",
      "kernel_id": "4677440"
    },
    {
      "ref": "jaehyeongan/jigsaw-toxicity-basic-embedding-lstm",
      "title": "Jigsaw toxicity - Basic Embedding+LSTM ",
      "source": "live",
      "kernel_id": "4637347"
    },
    {
      "ref": "marctorsoc/jigsaw-torchtext",
      "title": "Jigsaw torchtext",
      "source": "live",
      "kernel_id": "4592917"
    },
    {
      "ref": "kyakovlev/preprocessing-bert-public",
      "title": "Preprocessing BERT (public)",
      "source": "live",
      "kernel_id": "4549333"
    },
    {
      "ref": "kyakovlev/jigsaw-general-helper-public",
      "title": "Jigsaw general helper (public)",
      "source": "live",
      "kernel_id": "4549190"
    },
    {
      "ref": "kyakovlev/internal-eda-public",
      "title": "Internal EDA (public)",
      "source": "live",
      "kernel_id": "4546850"
    },
    {
      "ref": "hanyaopeng/single-bert-base-with-0-94376",
      "title": "single bert-base with 0.94376",
      "source": "live",
      "kernel_id": "4541647"
    },
    {
      "ref": "yuval6967/toxic-train-bert-base-pytorch",
      "title": "Toxic train BERT Base  pytorch",
      "source": "live",
      "kernel_id": "4540529"
    },
    {
      "ref": "mashhoori/a-loss-function-for-the-jigsaw-competition",
      "title": "A Loss function for the Jigsaw competition",
      "source": "live",
      "kernel_id": "4538286"
    },
    {
      "ref": "snakayama/fork-of-first-bert-model",
      "title": "Fork of FIRST BERT MODEL",
      "source": "live",
      "kernel_id": "4536838"
    },
    {
      "ref": "fulrose/inference-baseline-it-s-done",
      "title": "Inference Baseline - It's done..",
      "source": "live",
      "kernel_id": "4535833"
    },
    {
      "ref": "blackitten13/lstm-cp-clip-nb-tw-tfidf-bert4x-gpt-test-best",
      "title": "LSTM (cp clip nb tw) TFIDF BERT4x GPT (TEST) best",
      "source": "live",
      "kernel_id": "4532529"
    },
    {
      "ref": "chengjingye/lstm-cnn-3layer2d-bn",
      "title": "LSTM-CNN-3layer2d-BN",
      "source": "live",
      "kernel_id": "4529721"
    },
    {
      "ref": "yetman/simple-gru-bert",
      "title": "Simple GRU + BERT",
      "source": "live",
      "kernel_id": "4528949"
    },
    {
      "ref": "blackitten13/lstm-cp-clip-nb-tw-tfidf-berts-gpt-val2-best-r",
      "title": "LSTM (cp clip nb tw) TFIDF BERTs GPT (VAL2) best R",
      "source": "live",
      "kernel_id": "4528318"
    },
    {
      "ref": "matsuik/fork-of-pred-lstm-gpt2-bu12c45-lu0c1-ftpe18-7c1c82",
      "title": "Fork of PRED lstm gpt2 bu12C45 Lu0C1 FTPe18 7c1c82",
      "source": "live",
      "kernel_id": "4527865"
    },
    {
      "ref": "akhileshrai003/jigsaw-toxic-comment-classification",
      "title": "Jigsaw Toxic Comment Classification",
      "source": "live",
      "kernel_id": "4526843"
    },
    {
      "ref": "ostamand/submission-2-bert-gpt2",
      "title": "Submission #2: BERT + GPT2",
      "source": "live",
      "kernel_id": "4526094"
    },
    {
      "ref": "osciiart/character-level-cnn",
      "title": "Character-Level CNN",
      "source": "live",
      "kernel_id": "4525206"
    },
    {
      "ref": "shilparpns/jigsaw-starter-blend",
      "title": "jigsaw-starter-blend",
      "source": "live",
      "kernel_id": "4523300"
    },
    {
      "ref": "splacorn/submission1-inference-4-360-1-220",
      "title": "submission1_inference_4-360, 1-220",
      "source": "live",
      "kernel_id": "4515781"
    },
    {
      "ref": "snakayama/first-bert-model-yeahhhh",
      "title": "FIRST BERT MODEL YEAHHHH",
      "source": "live",
      "kernel_id": "4503550"
    },
    {
      "ref": "sakami/single-lstm-3rd-place",
      "title": "Single LSTM (3rd place)",
      "source": "live",
      "kernel_id": "4502115"
    },
    {
      "ref": "yosefardhito/eda-annotations-lexical-and-bag-of-words",
      "title": "EDA: Annotations, Lexical, and Bag-of-Words",
      "source": "live",
      "kernel_id": "4489559"
    },
    {
      "ref": "saileshmohanty/b-l-25-75",
      "title": "b_l_25_75",
      "source": "live",
      "kernel_id": "4486392"
    },
    {
      "ref": "tenffe/jigsaw-embedding-by-bert",
      "title": "jigsaw-embedding-by-BERT",
      "source": "live",
      "kernel_id": "4467842"
    },
    {
      "ref": "jacobgreen4477/optimize-lstm-easy-cut",
      "title": "optimize LSTM ++ (easy cut)",
      "source": "live",
      "kernel_id": "4467228"
    },
    {
      "ref": "rodgomrod/simple-lightgbm-stacker-identity-public-0-902",
      "title": "Simple LightGBM_Stacker_Identity [Public 0.902]",
      "source": "live",
      "kernel_id": "4463741"
    },
    {
      "ref": "blackitten13/bilstm-twitter-1-train-val",
      "title": "BiLSTM (Twitter); #1 (TRAIN/VAL)",
      "source": "live",
      "kernel_id": "4454740"
    },
    {
      "ref": "blackitten13/bilstm-numberbatch-0-train-val",
      "title": "BiLSTM (Numberbatch); #0 (TRAIN/VAL)",
      "source": "live",
      "kernel_id": "4446369"
    },
    {
      "ref": "ryches/leaderboard-analysis-with-4-days-left",
      "title": "Leaderboard Analysis with 4 days left",
      "source": "live",
      "kernel_id": "4444766"
    },
    {
      "ref": "gauravs90/keras-bert-toxic-model-bert-fine-tuning-with-keras",
      "title": "Keras Bert toxic model-Bert Fine tuning with Keras",
      "source": "live",
      "kernel_id": "4438220"
    },
    {
      "ref": "polarbearzyx/prj4ai-tersorflow-py",
      "title": "prj4AI-tersorflow-py",
      "source": "live",
      "kernel_id": "4436149"
    },
    {
      "ref": "polarbearzyx/filter-the-data",
      "title": "filter-the-data",
      "source": "live",
      "kernel_id": "4436081"
    },
    {
      "ref": "abdelrahmangamil/toxic-spark",
      "title": "toxic_spark",
      "source": "live",
      "kernel_id": "4432415"
    },
    {
      "ref": "weilinwuweilinwu/bidirectional-lstm-with-weighted-samples",
      "title": "Bidirectional LSTM with weighted samples",
      "source": "live",
      "kernel_id": "4432150"
    },
    {
      "ref": "tenffe/xlnet",
      "title": "xlnet",
      "source": "live",
      "kernel_id": "4430907"
    },
    {
      "ref": "blackitten13/bilstm-c-p-target-clip-0-05-5-ep-0-train-val",
      "title": "BiLSTM C P target clip 0.05; 5 ep, #0 (TRAIN/VAL)",
      "source": "live",
      "kernel_id": "4430869"
    },
    {
      "ref": "iezepov/wombat-inference-kernel",
      "title": "Wombat Inference Kernel",
      "source": "live",
      "kernel_id": "4429425"
    },
    {
      "ref": "juliakt/bert-model-prediction-maybe",
      "title": "bert_model_prediction_maybe",
      "source": "live",
      "kernel_id": "4428191"
    },
    {
      "ref": "polarbearzyx/prj3-for-ai-cookbook-tensorflow",
      "title": "prj3-for-AI-cookbook-tensorflow",
      "source": "live",
      "kernel_id": "4425888"
    },
    {
      "ref": "luischreiter/look-into-embedding-vectors-glove-fasttext-google",
      "title": "Look into Embedding Vectors-GloVe_FastText_Google",
      "source": "live",
      "kernel_id": "4425509"
    },
    {
      "ref": "codeastar/load-keras-rnn-model",
      "title": "Load Keras RNN model",
      "source": "live",
      "kernel_id": "4424501"
    },
    {
      "ref": "gphilmod/hello-world",
      "title": "hello world",
      "source": "live",
      "kernel_id": "4419089"
    },
    {
      "ref": "blackitten13/simple-tf-idf-models-train-val",
      "title": "Simple TF-IDF models (TRAIN/VAL)",
      "source": "live",
      "kernel_id": "4411655"
    },
    {
      "ref": "jigsawclassification/seoyounglstm",
      "title": "seoyounglstm",
      "source": "live",
      "kernel_id": "4405083"
    },
    {
      "ref": "vkurma/using-pretrained-models",
      "title": "Using pretrained models",
      "source": "live",
      "kernel_id": "4399029"
    },
    {
      "ref": "annekel/fastpreprocess-14min-99-7-coverage-gl-ov",
      "title": "FastPreprocess_14min_99.7%coverage_gl_ov",
      "source": "live",
      "kernel_id": "4395172"
    },
    {
      "ref": "blackitten13/fork-of-train-preprocessing-for-tf-idf",
      "title": "Fork of Train preprocessing for TF-IDF",
      "source": "live",
      "kernel_id": "4389162"
    },
    {
      "ref": "shubham505/simple-lstm-for-high-score",
      "title": "Simple LSTM for high score",
      "source": "live",
      "kernel_id": "4387755"
    },
    {
      "ref": "yaroshevskiy/bert-base-2-epochs",
      "title": "bert base 2 epochs",
      "source": "live",
      "kernel_id": "4374851"
    },
    {
      "ref": "polarbearzyx/ai-prj3",
      "title": "AI_prj3",
      "source": "live",
      "kernel_id": "4374063"
    },
    {
      "ref": "prabanch/jigsaw-unintended-bias-prediction",
      "title": "Jigsaw Unintended Bias prediction ",
      "source": "live",
      "kernel_id": "4372069"
    },
    {
      "ref": "prabanch/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "4370454"
    },
    {
      "ref": "polarbearzyx/project3-code",
      "title": "project3 code",
      "source": "live",
      "kernel_id": "4369523"
    },
    {
      "ref": "ayush99rox/bert-lstm-blend",
      "title": "BERT-LSTM-BLEND",
      "source": "live",
      "kernel_id": "4367679"
    },
    {
      "ref": "rashikds/hate-speach-identifying-hate-group-v2-svm",
      "title": "hate speach: identifying hate group - v2_svm",
      "source": "live",
      "kernel_id": "4367224"
    },
    {
      "ref": "codeastar/save-keras-rnn-model",
      "title": "Save Keras RNN model",
      "source": "live",
      "kernel_id": "4366422"
    },
    {
      "ref": "blackitten13/my-validation",
      "title": "My validation",
      "source": "live",
      "kernel_id": "4365363"
    },
    {
      "ref": "sharibkhan/my-first-semantic-analysis-problem-in-nlp",
      "title": "My First Semantic Analysis Problem In NLP",
      "source": "live",
      "kernel_id": "4362738"
    },
    {
      "ref": "saileshmohanty/lstm-1",
      "title": "LSTM_1",
      "source": "live",
      "kernel_id": "4361553"
    },
    {
      "ref": "saileshmohanty/bert-trial",
      "title": "BERT Trial",
      "source": "live",
      "kernel_id": "4360108"
    },
    {
      "ref": "prithvi1029/unprocessed-comments-worked-well",
      "title": "Unprocessed comments worked well",
      "source": "live",
      "kernel_id": "4357425"
    },
    {
      "ref": "tenffe/transform-tf-bert-to-pytorch-bert",
      "title": "transform TF BERT to pytorch BERT",
      "source": "live",
      "kernel_id": "4352960"
    },
    {
      "ref": "marinan67/kernel-kerasregressor-tfidf",
      "title": "kernel_kerasregressor_tfidf",
      "source": "live",
      "kernel_id": "4351581"
    },
    {
      "ref": "tenffe/fastai-bert-train-baseline-10-epoch",
      "title": "fastai-BERT-train-baseline-10-epoch",
      "source": "live",
      "kernel_id": "4351059"
    },
    {
      "ref": "tenffe/fastai-bert-inference-with-9-epoch",
      "title": "fastai-BERT-inference with 9 epoch",
      "source": "live",
      "kernel_id": "4350410"
    },
    {
      "ref": "dyyalex/jigsaw-starter-blend-with-bert-config",
      "title": "jigsaw-starter-blend with bert config",
      "source": "live",
      "kernel_id": "4350140"
    },
    {
      "ref": "blackitten13/bilstm-crawl-paragram-6-ep-0-train",
      "title": "BiLSTM (Crawl + Paragram); 6 ep, #0 (TRAIN)",
      "source": "live",
      "kernel_id": "4338053"
    },
    {
      "ref": "fanluwu/nb-jigsaw",
      "title": "NB-Jigsaw",
      "source": "live",
      "kernel_id": "4333863"
    },
    {
      "ref": "yeayates21/bert-v6",
      "title": "BERT_v6",
      "source": "live",
      "kernel_id": "4332030"
    },
    {
      "ref": "bkkaggle/jigsaw-preprocessing-gpt2-1",
      "title": "Jigsaw preprocessing gpt2 1",
      "source": "live",
      "kernel_id": "4328124"
    },
    {
      "ref": "sarveshsinghsvn/kernel451498e34a",
      "title": "kernel451498e34a",
      "source": "live",
      "kernel_id": "4327831"
    },
    {
      "ref": "nikhilroxtomar/usel-3-keras-lstm",
      "title": "USEL-3 & Keras LSTM",
      "source": "live",
      "kernel_id": "4326965"
    },
    {
      "ref": "haqishen/jigsaw-predict",
      "title": "Jigsaw_predict",
      "source": "live",
      "kernel_id": "4321942"
    },
    {
      "ref": "jt0321/fine-tuning-bert-with-mxnet-gluon",
      "title": "fine-tuning Bert with mxnet/gluon",
      "source": "live",
      "kernel_id": "4317730"
    },
    {
      "ref": "vaibhavmathur96/jigsaw-starter-blend",
      "title": "jigsaw-starter-blend",
      "source": "live",
      "kernel_id": "4309220"
    },
    {
      "ref": "maxjeblick/replacing-oov-words-with-bert",
      "title": "Replacing OOV words with BERT ",
      "source": "live",
      "kernel_id": "4299015"
    },
    {
      "ref": "jasonjensen/tensorflow-bert",
      "title": "TensorFlow BERT",
      "source": "live",
      "kernel_id": "4297249"
    },
    {
      "ref": "shubham505/keras-lstm-5-fold",
      "title": "keras lstm +5-fold",
      "source": "live",
      "kernel_id": "4290378"
    },
    {
      "ref": "sanjeeth/logreg-nb-text-classification",
      "title": "LogReg_NB Text classification",
      "source": "live",
      "kernel_id": "4288786"
    },
    {
      "ref": "vendredi218/lstm-v1",
      "title": "LSTM-v1",
      "source": "live",
      "kernel_id": "4287665"
    },
    {
      "ref": "nikhilroxtomar/bi-gru-lstm-cnn-fasttext",
      "title": "Bi-GRU-LSTM-CNN-FastText",
      "source": "live",
      "kernel_id": "4286506"
    },
    {
      "ref": "takumiito/bert-lstm-rank-blender-commented",
      "title": "BERT + LSTM (rank blender)_commented",
      "source": "live",
      "kernel_id": "4283852"
    },
    {
      "ref": "k123321141/bert-baseline",
      "title": "bert baseline",
      "source": "live",
      "kernel_id": "4279100"
    },
    {
      "ref": "sklasfeld/simple-lstm-skeleton-sk-v1",
      "title": "Simple_LSTM_Skeleton_SK_V1",
      "source": "live",
      "kernel_id": "4277928"
    },
    {
      "ref": "anjing/nlp-preprocessor-and-ida",
      "title": "NLP_preprocessor_and_IDA",
      "source": "live",
      "kernel_id": "4268291"
    },
    {
      "ref": "infoabhitech/jigsaw-toxic-classification-keras-nn",
      "title": "Jigsaw Toxic Classification(Keras NN)",
      "source": "live",
      "kernel_id": "4266521"
    },
    {
      "ref": "liyushihaoren2/gpt2-0-uncased",
      "title": "GPT2.0 uncased",
      "source": "live",
      "kernel_id": "4266335"
    },
    {
      "ref": "bkkaggle/converting-whole-word-masking-bert-to-pytorch",
      "title": "converting whole-word-masking bert to pytorch",
      "source": "live",
      "kernel_id": "4260290"
    },
    {
      "ref": "aussie84/basic-lstm-explanatory-walkthrough",
      "title": "Basic LSTM: Explanatory walkthrough",
      "source": "live",
      "kernel_id": "4253959"
    },
    {
      "ref": "penpen86/pytorch-bert-inference-22ec03",
      "title": "Pytorch BERT Inference 22ec03",
      "source": "live",
      "kernel_id": "4250828"
    },
    {
      "ref": "freddo1one/simple-logistic-regresssion",
      "title": "Simple logistic regresssion",
      "source": "live",
      "kernel_id": "4239399"
    },
    {
      "ref": "jaharrin/logistic-regression-with-tf-idf",
      "title": "Logistic Regression with TF-IDF",
      "source": "live",
      "kernel_id": "4238852"
    },
    {
      "ref": "tomkpace/bow-svd-knn-as-a-weak-learner",
      "title": "BOW SVD KNN as a Weak Learner",
      "source": "live",
      "kernel_id": "4214426"
    },
    {
      "ref": "alexgeiger/train-bert-model-7-input",
      "title": "TRAIN BERT MODEL 7 Input",
      "source": "live",
      "kernel_id": "4210406"
    },
    {
      "ref": "hatunina/lstm-with-normal-features-base-on-dieter",
      "title": "LSTM with normal features base on Dieter",
      "source": "live",
      "kernel_id": "4210159"
    },
    {
      "ref": "jasonjensen/remove-identity-words-simple-lstm",
      "title": "Remove identity-words + simple LSTM",
      "source": "live",
      "kernel_id": "4209934"
    },
    {
      "ref": "cuijinghuan/kernel8c6d4caaf4",
      "title": "kernel8c6d4caaf4",
      "source": "live",
      "kernel_id": "4208261"
    },
    {
      "ref": "cuijinghuan/kernel9dd7d93aaf",
      "title": "kernel9dd7d93aaf",
      "source": "live",
      "kernel_id": "4206928"
    },
    {
      "ref": "saurabh7/bert-1050000-large",
      "title": "BERT - 1050000- Large",
      "source": "live",
      "kernel_id": "4206152"
    },
    {
      "ref": "chriscc/jigsaw-starter-blend",
      "title": "jigsaw-starter-blend",
      "source": "live",
      "kernel_id": "4201811"
    },
    {
      "ref": "w835332003/jigsawv8",
      "title": "jigsawv8",
      "source": "live",
      "kernel_id": "4201319"
    },
    {
      "ref": "cuijinghuan/kernel84a86254a8",
      "title": "kernel84a86254a8",
      "source": "live",
      "kernel_id": "4198289"
    },
    {
      "ref": "elyliu/pytorch-bert-inference-63d1e5",
      "title": "Pytorch BERT Inference 63d1e5",
      "source": "live",
      "kernel_id": "4194264"
    },
    {
      "ref": "aialba/lstm-w-pytorch",
      "title": "LSTM w/ Pytorch",
      "source": "live",
      "kernel_id": "4192486"
    },
    {
      "ref": "danich329/simple-lstm-skeleton",
      "title": "Simple_LSTM_Skeleton",
      "source": "live",
      "kernel_id": "4190628"
    },
    {
      "ref": "isikkuntay/glove-n-bert-test",
      "title": "glove n bert  test",
      "source": "live",
      "kernel_id": "4189676"
    },
    {
      "ref": "hzk123/total-preprocess",
      "title": "total_preprocess",
      "source": "live",
      "kernel_id": "4176382"
    },
    {
      "ref": "yangsaewon/lstm-kfold-training",
      "title": "lstm_kfold_training",
      "source": "live",
      "kernel_id": "4170421"
    },
    {
      "ref": "yangsaewon/bert-lstm-inference",
      "title": "bert_lstm_inference",
      "source": "live",
      "kernel_id": "4168389"
    },
    {
      "ref": "spell0/jigsaw-toxicity",
      "title": "jigsaw_toxicity",
      "source": "live",
      "kernel_id": "4163846"
    },
    {
      "ref": "soulmachine/jigsaw-utils",
      "title": "jigsaw-utils",
      "source": "live",
      "kernel_id": "4163754"
    },
    {
      "ref": "chetnapannu/toxicity-classification-eda",
      "title": "Toxicity Classification - EDA",
      "source": "live",
      "kernel_id": "4161536"
    },
    {
      "ref": "matsuik/convert-embedding-dictionary-to-gensim-w2v-format",
      "title": "Convert embedding dictionary to gensim w2v format",
      "source": "live",
      "kernel_id": "4158544"
    },
    {
      "ref": "chechir/bert-lstm-rank-blender",
      "title": "BERT + LSTM (rank blender)",
      "source": "live",
      "kernel_id": "4154746"
    },
    {
      "ref": "siddhrath/all-zero",
      "title": "all_zero",
      "source": "live",
      "kernel_id": "4148903"
    },
    {
      "ref": "siddhrath/double-model",
      "title": "Double_model",
      "source": "live",
      "kernel_id": "4148570"
    },
    {
      "ref": "bernalca/exploration-jigsaw-toxicity-classification",
      "title": "[Exploration] Jigsaw Toxicity Classification ",
      "source": "live",
      "kernel_id": "4146984"
    },
    {
      "ref": "carrot6869/lstm-preprocess",
      "title": "lstm+preprocess",
      "source": "live",
      "kernel_id": "4143497"
    },
    {
      "ref": "ruhong/jigsaw-unintended-bias-simple-lstm-pytorch",
      "title": "jigsaw-unintended-bias-simple-lstm-pytorch",
      "source": "live",
      "kernel_id": "4137347"
    },
    {
      "ref": "ruhong/jigsaw-unintended-bias-simple-lstm",
      "title": "jigsaw-unintended-bias-simple-lstm",
      "source": "live",
      "kernel_id": "4136954"
    },
    {
      "ref": "hhzzxx957/fork-of-toxic-bert-plain-vanila",
      "title": "Fork of Toxic  BERT plain vanila",
      "source": "live",
      "kernel_id": "4136351"
    },
    {
      "ref": "siddhrath/first-model-lstm",
      "title": "first_model_lstm",
      "source": "live",
      "kernel_id": "4136243"
    },
    {
      "ref": "ruhong/jigsaw-unintended-bias-bert-pytorch",
      "title": "jigsaw-unintended-bias-bert-pytorch",
      "source": "live",
      "kernel_id": "4136242"
    },
    {
      "ref": "niel96/simple-classification-algorithm",
      "title": "Simple Classification Algorithm",
      "source": "live",
      "kernel_id": "4132571"
    },
    {
      "ref": "shivamkotwalia/jigsaw-unintended-bias-in-toxicity",
      "title": "Jigsaw_Unintended_Bias_in_Toxicity",
      "source": "live",
      "kernel_id": "4130654"
    },
    {
      "ref": "dalip98/simple-lstm-keras",
      "title": "Simple LSTM -Keras",
      "source": "live",
      "kernel_id": "4118500"
    },
    {
      "ref": "s7anmerk/lean-import-to-save-ram-and-eda",
      "title": "Lean import to save RAM and EDA",
      "source": "live",
      "kernel_id": "4116906"
    },
    {
      "ref": "tides94/word-rank-kernel",
      "title": "Word rank kernel",
      "source": "live",
      "kernel_id": "4109227"
    },
    {
      "ref": "chriscc/jigsaw-starter",
      "title": "jigsaw-starter",
      "source": "live",
      "kernel_id": "4105761"
    },
    {
      "ref": "aminejait/jigsaw-bert",
      "title": "jigsaw bert",
      "source": "live",
      "kernel_id": "4101479"
    },
    {
      "ref": "ankitscience/elmo-with-attention-bilstm-including-id-parameter",
      "title": "Elmo with Attention& BiLSTM including ID Parameter",
      "source": "live",
      "kernel_id": "4098661"
    },
    {
      "ref": "tanreinama/fastai-file-stream-training",
      "title": "fastai file stream training",
      "source": "live",
      "kernel_id": "4092455"
    },
    {
      "ref": "timon88/bert-lstm-simple-blender-0-93844-lb",
      "title": "BERT + LSTM (simple blender) - 0.93844 LB",
      "source": "live",
      "kernel_id": "4085485"
    },
    {
      "ref": "ruhong/jigsaw-unintended-bias-baseline-cnn",
      "title": "jigsaw-unintended-bias-baseline-cnn",
      "source": "live",
      "kernel_id": "4080142"
    },
    {
      "ref": "vaslem/fixed-preprocessing",
      "title": "Fixed preprocessing",
      "source": "live",
      "kernel_id": "4077293"
    },
    {
      "ref": "sanjayroberts1/lstm-toxic-comments",
      "title": "LSTM Toxic Comments",
      "source": "live",
      "kernel_id": "4061895"
    },
    {
      "ref": "phseidl/pytorch-bert-fast-bucket-inference-blend-individ",
      "title": "Pytorch BERT Fast Bucket Inference Blend individ",
      "source": "live",
      "kernel_id": "4061876"
    },
    {
      "ref": "levysouza/amkernelproject",
      "title": "AMKernelProject",
      "source": "live",
      "kernel_id": "4059969"
    },
    {
      "ref": "qhd0081/test-bert",
      "title": "Test Bert",
      "source": "live",
      "kernel_id": "4054360"
    },
    {
      "ref": "soulmachine/jigsaw-pytorch-bert",
      "title": "jigsaw-pytorch-bert",
      "source": "live",
      "kernel_id": "4052902"
    },
    {
      "ref": "tanreinama/pretext-lstm-tuning-v3-with-ensemble-tune",
      "title": "PreText-LSTM-Tuning v3 with ensemble tune",
      "source": "live",
      "kernel_id": "4051445"
    },
    {
      "ref": "surbhibhardwaj/kernelb3c83b7be2",
      "title": "kernelb3c83b7be2",
      "source": "live",
      "kernel_id": "4043458"
    },
    {
      "ref": "rutvik04/jigsaw-unintended-bias-toxicity-classification",
      "title": "Jigsaw Unintended Bias Toxicity Classification",
      "source": "live",
      "kernel_id": "4040009"
    },
    {
      "ref": "sanjayroberts1/sklearn-algorithms-toxic-comments",
      "title": "SKLearn Algorithms -- Toxic Comments",
      "source": "live",
      "kernel_id": "4036393"
    },
    {
      "ref": "kdgyun425/a-variant-of-transformer",
      "title": "A variant of Transformer",
      "source": "live",
      "kernel_id": "4033606"
    },
    {
      "ref": "kabure/simple-eda-hard-views-w-easy-code",
      "title": "Simple EDA - Hard views w/ Easy code",
      "source": "live",
      "kernel_id": "4032644"
    },
    {
      "ref": "arcticmarmot/using-conv1d-and-gru",
      "title": "Using Conv1D and GRU",
      "source": "live",
      "kernel_id": "4032066"
    },
    {
      "ref": "johnmollas/kernelff5eaed6ec",
      "title": "kernelff5eaed6ec",
      "source": "live",
      "kernel_id": "4030851"
    },
    {
      "ref": "yeayates21/threshold-eda-then-following-the-rabbit",
      "title": "Threshold_EDA_Then_Following_The_Rabbit",
      "source": "live",
      "kernel_id": "4025924"
    },
    {
      "ref": "uysimty/simple-toxicity-classification-submission",
      "title": "Simple Toxicity Classification (Submission)",
      "source": "live",
      "kernel_id": "4023159"
    },
    {
      "ref": "kishore6157/jigsaw-toxicity-classification-lstm-v4",
      "title": "Jigsaw_Toxicity_Classification_LSTM_v4",
      "source": "live",
      "kernel_id": "4012253"
    },
    {
      "ref": "praritlamba/simple-lstm-v2-max-len-300",
      "title": "simple_lstm_v2_max_len_300",
      "source": "live",
      "kernel_id": "4001815"
    },
    {
      "ref": "sameerdev7/90-accuracy-using-double-lstm",
      "title": "[90%] Accuracy using Double LSTM",
      "source": "live",
      "kernel_id": "3999002"
    },
    {
      "ref": "kishore6157/jigsaw-toxicity-classification",
      "title": "Jigsaw_Toxicity_Classification",
      "source": "live",
      "kernel_id": "3990164"
    },
    {
      "ref": "timidli0n/defaultlstm",
      "title": "DefaultLSTM",
      "source": "live",
      "kernel_id": "3985727"
    },
    {
      "ref": "rafay12/jigsaw-competition-12",
      "title": "jigsaw competition ---12",
      "source": "live",
      "kernel_id": "3985544"
    },
    {
      "ref": "godeye/kernelf66a675087",
      "title": "kernelf66a675087",
      "source": "live",
      "kernel_id": "3982502"
    },
    {
      "ref": "ravikondadadi/loading-bert-using-pytorch-with-tokenizer-apex",
      "title": "Loading BERT using pytorch (with tokenizer & apex)",
      "source": "live",
      "kernel_id": "3982347"
    },
    {
      "ref": "proyectomineria2019/kernel9b764d76f5",
      "title": "kernel9b764d76f5",
      "source": "live",
      "kernel_id": "3966606"
    },
    {
      "ref": "rangaritab/kernelb79e9290dc",
      "title": "kernelb79e9290dc",
      "source": "live",
      "kernel_id": "3965696"
    },
    {
      "ref": "luisk1504/kernel8b0f797879-2",
      "title": "kernel8b0f797879-2",
      "source": "live",
      "kernel_id": "3965048"
    },
    {
      "ref": "cristinasierra/pretext-lstm-tuning-v3",
      "title": "PreText-LSTM-Tuning v3",
      "source": "live",
      "kernel_id": "3963668"
    },
    {
      "ref": "luisk1504/kernel0f620054e3",
      "title": "kernel0f620054e3",
      "source": "live",
      "kernel_id": "3963412"
    },
    {
      "ref": "hvjaime/kernel2d3a6ba71d",
      "title": "kernel2d3a6ba71d",
      "source": "live",
      "kernel_id": "3958747"
    },
    {
      "ref": "fortizs/simple-lstm-with-identity-parameters-fastai",
      "title": "Simple LSTM with Identity Parameters - FastAI",
      "source": "live",
      "kernel_id": "3956734"
    },
    {
      "ref": "afmartinezt/miia-submit-2",
      "title": " MIIA - Submit # 2",
      "source": "live",
      "kernel_id": "3956181"
    },
    {
      "ref": "andaoba1/preproccesing-and-cudnnlstm",
      "title": "Preproccesing and CuDNNLSTM",
      "source": "live",
      "kernel_id": "3953497"
    },
    {
      "ref": "jacobgreen4477/dms-korea-simple-eda",
      "title": "DMS.KOREA - simple eda",
      "source": "live",
      "kernel_id": "3951129"
    },
    {
      "ref": "jacobgreen4477/dms-korea-clean-text-glove-fasttext-keras",
      "title": " DMS.KOREA - clean-text+glove+fasttext+keras",
      "source": "live",
      "kernel_id": "3947595"
    },
    {
      "ref": "cabarajasb2019/second",
      "title": "Second ",
      "source": "live",
      "kernel_id": "3946950"
    },
    {
      "ref": "gaguerrerora/miia-p3",
      "title": "MIIA_P3",
      "source": "live",
      "kernel_id": "3946530"
    },
    {
      "ref": "afmartinezt/miia-submit-1",
      "title": "MIIA - Submit # 1",
      "source": "live",
      "kernel_id": "3945621"
    },
    {
      "ref": "ddw02141/simple-lstm-attention",
      "title": "Simple LSTM + Attention ",
      "source": "live",
      "kernel_id": "3943274"
    },
    {
      "ref": "sukpyohong/lstm1st",
      "title": "lstm1st",
      "source": "live",
      "kernel_id": "3943093"
    },
    {
      "ref": "gali1eo/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "3943062"
    },
    {
      "ref": "cantinier/kernel6c33af44d9",
      "title": "kernel6c33af44d9",
      "source": "live",
      "kernel_id": "3939223"
    },
    {
      "ref": "arcisad/keras-bidirectional-lstm-self-attention",
      "title": "Keras Bidirectional LSTM + Self-Attention",
      "source": "live",
      "kernel_id": "3936150"
    },
    {
      "ref": "manmohan123/kernel97688d5835",
      "title": "kernel97688d5835",
      "source": "live",
      "kernel_id": "3935020"
    },
    {
      "ref": "abhishek/pytorch-bert-inference",
      "title": "Pytorch BERT Inference",
      "source": "live",
      "kernel_id": "3933961"
    },
    {
      "ref": "ankuraman1234/toxic-classification-in-r-use-glm-to-predict",
      "title": "Toxic Classification in R use glm to predict",
      "source": "live",
      "kernel_id": "3928561"
    },
    {
      "ref": "yuval6967/toxic-bert-plain-vanila",
      "title": "Toxic  BERT plain vanila",
      "source": "live",
      "kernel_id": "3924879"
    },
    {
      "ref": "tofutiger/kernel2ac29febc6",
      "title": "kernel2ac29febc6",
      "source": "live",
      "kernel_id": "3924522"
    },
    {
      "ref": "andaoba1/ensayo-p3",
      "title": "Ensayo P3",
      "source": "live",
      "kernel_id": "3915533"
    },
    {
      "ref": "darestrepov/model1-naive-bayes-with-logreg",
      "title": "Model1 (Naive Bayes with Logreg) ",
      "source": "live",
      "kernel_id": "3914635"
    },
    {
      "ref": "vaslem/test-on-toy-jigsaw-with-1-entangledbilstm",
      "title": "Test on Toy Jigsaw with 1 EntangledBiLSTM",
      "source": "live",
      "kernel_id": "3913620"
    },
    {
      "ref": "vaslem/test-on-toy-jigsaw-with-entangledbilstm",
      "title": "Test on Toy Jigsaw with EntangledBiLSTM",
      "source": "live",
      "kernel_id": "3912725"
    },
    {
      "ref": "duykhanh99/lstm-fast-ai-tuning",
      "title": "LSTM - fast AI tuning",
      "source": "live",
      "kernel_id": "3909954"
    },
    {
      "ref": "abimannan/lstm-with-parameters",
      "title": "LSTM with parameters",
      "source": "live",
      "kernel_id": "3906966"
    },
    {
      "ref": "rangaritab/p3-team12-v3",
      "title": "P3-Team12_v3",
      "source": "live",
      "kernel_id": "3899849"
    },
    {
      "ref": "praxitelisk/jigsaw-toxicity-classification-eda-dl-keras-lstm",
      "title": "Jigsaw Toxicity Classification EDA + DL Keras LSTM",
      "source": "live",
      "kernel_id": "3899259"
    },
    {
      "ref": "duykhanh99/introduction-to-nlp-hust",
      "title": "Introduction to NLP hust",
      "source": "live",
      "kernel_id": "3894959"
    },
    {
      "ref": "gjeffroy/simple-model-naive-bayes-and-logistic-reg",
      "title": "Simple model (Naive Bayes and Logistic reg) ",
      "source": "live",
      "kernel_id": "3894809"
    },
    {
      "ref": "vaslem/test-on-toy-jigsaw",
      "title": "Test on Toy Jigsaw",
      "source": "live",
      "kernel_id": "3893106"
    },
    {
      "ref": "shubham505/apply-by-simple-bilstm",
      "title": "apply by Simple BiLSTM",
      "source": "live",
      "kernel_id": "3892867"
    },
    {
      "ref": "christofhenkel/how-to-preprocessing-for-glove-part2-usage",
      "title": "How To: Preprocessing for GloVe Part2: Usage",
      "source": "live",
      "kernel_id": "3890344"
    },
    {
      "ref": "springmanndaniel/baseline-in-r-lstm-cnns",
      "title": "baseline in R - lstm + cnns",
      "source": "live",
      "kernel_id": "3889952"
    },
    {
      "ref": "lfrincon90/kernel3b4efc9320",
      "title": "kernel3b4efc9320",
      "source": "live",
      "kernel_id": "3888425"
    },
    {
      "ref": "abhishek/convert-lines-faster-for-bert",
      "title": "Convert lines faster for BERT",
      "source": "live",
      "kernel_id": "3885989"
    },
    {
      "ref": "christofhenkel/how-to-preprocessing-for-glove-part1-eda",
      "title": "How To: Preprocessing for GloVe Part1: EDA",
      "source": "live",
      "kernel_id": "3885292"
    },
    {
      "ref": "hiromoon166/load-bert-fine-tuning-model",
      "title": "Load BERT fine-tuning model",
      "source": "live",
      "kernel_id": "3883616"
    },
    {
      "ref": "hiromoon166/save-bert-fine-tuning-model",
      "title": "Save BERT fine-tuning model",
      "source": "live",
      "kernel_id": "3883556"
    },
    {
      "ref": "gali1eo/pytorch-augmented-benchmark-kernel",
      "title": "PyTorch Augmented Benchmark Kernel",
      "source": "live",
      "kernel_id": "3882972"
    },
    {
      "ref": "thinhn/data-sci-embedding-bidirectional-lstm",
      "title": "Data Sci Embedding +Bidirectional LSTM",
      "source": "live",
      "kernel_id": "3878525"
    },
    {
      "ref": "tomkpace/simple-nn-starter-kernel",
      "title": "Simple NN Starter Kernel",
      "source": "live",
      "kernel_id": "3877729"
    },
    {
      "ref": "prakhar21god/toxic-classification-bias-visualization",
      "title": "toxic classification bias visualization",
      "source": "live",
      "kernel_id": "3875431"
    },
    {
      "ref": "rashikds/hate-speach-identifying-hate-group",
      "title": "hate speach: identifying hate group",
      "source": "live",
      "kernel_id": "3872454"
    },
    {
      "ref": "firstanton/nlp-build-embedding-matrix-without-full-pre-load",
      "title": "NLP Build Embedding Matrix, without full pre-load ",
      "source": "live",
      "kernel_id": "3869736"
    },
    {
      "ref": "chriskeown/lstm-2-64-pool-max-avg-dense-256-closs-fnl",
      "title": "LSTM: 2*64; Pool: Max, Avg; Dense:  256; closs FNL",
      "source": "live",
      "kernel_id": "3868747"
    },
    {
      "ref": "yeayates21/jigsaw-vae-v2",
      "title": "Jigsaw_VAE_v2",
      "source": "live",
      "kernel_id": "3867880"
    },
    {
      "ref": "liaojh1998/toxic-broccoli-lstm-with-preprocessing",
      "title": "toxic-broccoli-lstm-with-preprocessing",
      "source": "live",
      "kernel_id": "3867669"
    },
    {
      "ref": "nz0722/reasoning-some-text-clean-not-work",
      "title": "Reasoning Some Text Clean Not Work",
      "source": "live",
      "kernel_id": "3858909"
    },
    {
      "ref": "chriskeown/lstm-64-pool-max-avg-dense-256-custom-cost",
      "title": "LSTM: 64; Pool: Max, Avg; Dense: 256; Custom Cost",
      "source": "live",
      "kernel_id": "3857355"
    },
    {
      "ref": "farjadk/nlp-hatespeach-target-type-identification",
      "title": "NLP - Hatespeach Target Type Identification",
      "source": "live",
      "kernel_id": "3854337"
    },
    {
      "ref": "nevs1973/newbie-tutorial-jigsaw-unintended-bias-basic-eda",
      "title": "Newbie Tutorial - Jigsaw Unintended Bias Basic EDA",
      "source": "live",
      "kernel_id": "3852204"
    },
    {
      "ref": "woainilin/kernel2221a225b3",
      "title": "kernel2221a225b3",
      "source": "live",
      "kernel_id": "3839473"
    },
    {
      "ref": "xiespeng/kernel4b01d755dd",
      "title": "kernel4b01d755dd",
      "source": "live",
      "kernel_id": "3838794"
    },
    {
      "ref": "protan/lstm-cnn-torchtext-with-ignite",
      "title": "LSTM + CNN (torchtext with ignite)",
      "source": "live",
      "kernel_id": "3836247"
    },
    {
      "ref": "maxjeblick/text-augmentation",
      "title": "Text augmentation",
      "source": "live",
      "kernel_id": "3832182"
    },
    {
      "ref": "tarunpaparaju/jigsaw-competition-more-text-cleaning",
      "title": "Jigsaw Competition : More Text Cleaning",
      "source": "live",
      "kernel_id": "3828275"
    },
    {
      "ref": "lachonman/fastai-lm-on-extended-dataset-cv-regression",
      "title": "FastAI LM on extended dataset+CV Regression",
      "source": "live",
      "kernel_id": "3826105"
    },
    {
      "ref": "chriskeown/lstm-64-pool-max-avg-dense-256",
      "title": "LSTM: 64; Pool: Max, Avg; Dense: 256",
      "source": "live",
      "kernel_id": "3823041"
    },
    {
      "ref": "chriskeown/bilstm-2-128-pool-max-avg-dense-512",
      "title": "BiLSTM: 2*128; Pool: Max, Avg; Dense: 512",
      "source": "live",
      "kernel_id": "3822908"
    },
    {
      "ref": "beautifulsoup4/bilstm-0-6lrsched-identity-customloss",
      "title": "BiLSTM_0.6lrsched_identity_customloss",
      "source": "live",
      "kernel_id": "3820170"
    },
    {
      "ref": "sinchir0/simple-eda-for-jigsaw",
      "title": "Simple EDA for Jigsaw",
      "source": "live",
      "kernel_id": "3815095"
    },
    {
      "ref": "currie32/ulmfit-fastai",
      "title": "ulmfit - fastai",
      "source": "live",
      "kernel_id": "3813799"
    },
    {
      "ref": "iavinas/toxicity-bias-tfidfvectorizer",
      "title": "Toxicity Bias TfidfVectorizer",
      "source": "live",
      "kernel_id": "3812760"
    },
    {
      "ref": "duykhanh99/bidirectional-lstm-and-attention",
      "title": "Bidirectional LSTM and Attention",
      "source": "live",
      "kernel_id": "3812017"
    },
    {
      "ref": "mshaked/666-666",
      "title": "666 ¯\\_(ツ)_/¯ 666",
      "source": "live",
      "kernel_id": "3811727"
    },
    {
      "ref": "farjadk/kernelb013a8a11e",
      "title": "kernelb013a8a11e",
      "source": "live",
      "kernel_id": "3809559"
    },
    {
      "ref": "alexanderliao/insight-eda-distributions",
      "title": "Insight EDA-Distributions",
      "source": "live",
      "kernel_id": "3804734"
    },
    {
      "ref": "duykhanh99/bidirectional-lstm-attention",
      "title": "Bidirectional LSTM+ Attention",
      "source": "live",
      "kernel_id": "3799338"
    },
    {
      "ref": "hydrilla/kerneld016f7f293",
      "title": "kerneld016f7f293",
      "source": "live",
      "kernel_id": "3796056"
    },
    {
      "ref": "artgor/pytorch-text-processing-and-other-things",
      "title": "Pytorch text processing and other things",
      "source": "live",
      "kernel_id": "3795681"
    },
    {
      "ref": "lenapiter/basic-approach-with-spacy-and-gensim",
      "title": "Basic Approach with spaCy and gensim ",
      "source": "live",
      "kernel_id": "3793573"
    },
    {
      "ref": "kenkrige/subgroup-analysis",
      "title": "Subgroup Analysis",
      "source": "live",
      "kernel_id": "3790122"
    },
    {
      "ref": "albahnsen/p3-samplesolution",
      "title": "P3-SampleSolution",
      "source": "live",
      "kernel_id": "3786637"
    },
    {
      "ref": "ekhtiar/unintended-eda-with-tutorial-notes",
      "title": "Unintended EDA [with Tutorial Notes]",
      "source": "live",
      "kernel_id": "3783393"
    },
    {
      "ref": "sklasfeld/simple-lstm-annotated-v2",
      "title": "Simple_LSTM_annotated_V2",
      "source": "live",
      "kernel_id": "3781385"
    },
    {
      "ref": "pnussbaum/benchmark-kernel-and-aaa19-v06",
      "title": "Benchmark Kernel and AAA19 v06",
      "source": "live",
      "kernel_id": "3779889"
    },
    {
      "ref": "peterjaq/bigru-demo",
      "title": "BiGRU demo",
      "source": "live",
      "kernel_id": "3770795"
    },
    {
      "ref": "takafumif/lstm-model",
      "title": "LSTM_model",
      "source": "live",
      "kernel_id": "3769984"
    },
    {
      "ref": "sklasfeld/predict-toxicity-v1",
      "title": "Predict_Toxicity_V1",
      "source": "live",
      "kernel_id": "3769297"
    },
    {
      "ref": "artgor/pytorch-text-processing-and-other-things-old",
      "title": "Pytorch, text processing and other things old",
      "source": "live",
      "kernel_id": "3765668"
    },
    {
      "ref": "samarthsarin/lstm-with-text-cleaning",
      "title": "LSTM with Text Cleaning",
      "source": "live",
      "kernel_id": "3753969"
    },
    {
      "ref": "adrianoavelar/lstm-eda-solution-for-jigsaw-toxicity",
      "title": "LSTM -EDA-Solution for Jigsaw ... Toxicity",
      "source": "live",
      "kernel_id": "3751592"
    },
    {
      "ref": "neel783d/keras-lstm-model-without-pretrained-embedding",
      "title": "Keras LSTM Model without Pretrained Embedding",
      "source": "live",
      "kernel_id": "3742684"
    },
    {
      "ref": "gilads/dnn1-gilad",
      "title": "DNN1_gilad",
      "source": "live",
      "kernel_id": "3738973"
    },
    {
      "ref": "jaehyeongan/jigsaw-toxicity-very-simple-embedding-lstm",
      "title": "Jigsaw toxicity - very simple Embedding+LSTM ",
      "source": "live",
      "kernel_id": "3729226"
    },
    {
      "ref": "ivansv/text-mining-toxicity",
      "title": "Text mining_toxicity",
      "source": "live",
      "kernel_id": "3727902"
    },
    {
      "ref": "occuromist/occuromist-pub",
      "title": "occuromist_pub",
      "source": "live",
      "kernel_id": "3724551"
    },
    {
      "ref": "kenkrige/bert-inference-for-upload",
      "title": "BERT Inference for upload",
      "source": "live",
      "kernel_id": "3720682"
    },
    {
      "ref": "xiicwo/simple-lstm-with-r",
      "title": "Simple LSTM with R",
      "source": "live",
      "kernel_id": "3718451"
    },
    {
      "ref": "xjie123456/kernel3f7f09718c",
      "title": "kernel3f7f09718c",
      "source": "live",
      "kernel_id": "3717542"
    },
    {
      "ref": "maxl28618/toxic-comments-lstm-in-pytorch-with-torchtext",
      "title": "Toxic comments - LSTM in PyTorch with TorchText",
      "source": "live",
      "kernel_id": "3717325"
    },
    {
      "ref": "kumarmanish/jigsaw-fast-compact-solution",
      "title": "Jigsaw Fast Compact Solution",
      "source": "live",
      "kernel_id": "3711993"
    },
    {
      "ref": "duykhanh99/nlp-basic",
      "title": "NLP basic",
      "source": "live",
      "kernel_id": "3709727"
    },
    {
      "ref": "jingw222/jigsaw",
      "title": "jigsaw",
      "source": "live",
      "kernel_id": "3708176"
    },
    {
      "ref": "sarvajna/jigsaw-toxicity-eda",
      "title": "Jigsaw Toxicity - EDA",
      "source": "live",
      "kernel_id": "3706515"
    },
    {
      "ref": "mvpvalues/auc-calculations-with-rounding-at-beginning",
      "title": "AUC calculations with rounding at beginning",
      "source": "live",
      "kernel_id": "3704586"
    },
    {
      "ref": "nklinzhiming/pytorch-base-model-99c811",
      "title": "PyTorch base model 99c811",
      "source": "live",
      "kernel_id": "3698117"
    },
    {
      "ref": "christofhenkel/temporal-cnn",
      "title": "Temporal CNN",
      "source": "live",
      "kernel_id": "3697284"
    },
    {
      "ref": "sklasfeld/beginner-modeling",
      "title": "Beginner Modeling",
      "source": "live",
      "kernel_id": "3696075"
    },
    {
      "ref": "sklasfeld/basic-exploratory-analysis",
      "title": "Basic exploratory analysis",
      "source": "live",
      "kernel_id": "3695693"
    },
    {
      "ref": "skumar2007ctae/text-pre-processing-applied-simple-lstm",
      "title": "Text pre processing applied -Simple LSTM ",
      "source": "live",
      "kernel_id": "3687471"
    },
    {
      "ref": "buntyshah/jigsaw-memory-optimization-upto-40",
      "title": "Jigsaw - Memory Optimization upto 40%",
      "source": "live",
      "kernel_id": "3682403"
    },
    {
      "ref": "tarunpaparaju/jigsaw-competition-google-perspective-api",
      "title": "Jigsaw Competition : Google Perspective API",
      "source": "live",
      "kernel_id": "3677247"
    },
    {
      "ref": "firstanton/nlp-func-for-determining-dictionary-coverage",
      "title": "NLP Func for determining dictionary coverage",
      "source": "live",
      "kernel_id": "3673843"
    },
    {
      "ref": "yeayates21/jigsaw-simple-text-features-and-h2o-v4",
      "title": "Jigsaw_Simple_Text_Features_and_H2O_v4",
      "source": "live",
      "kernel_id": "3671648"
    },
    {
      "ref": "cibi075/kernal-cb-t",
      "title": "kernal_cb(T)",
      "source": "live",
      "kernel_id": "3671641"
    },
    {
      "ref": "shilowu/weightedforsubmetric",
      "title": "WeightedForSubmetric",
      "source": "live",
      "kernel_id": "3669587"
    },
    {
      "ref": "fafiab/kernelb5f3536e06",
      "title": "kernelb5f3536e06",
      "source": "live",
      "kernel_id": "3668376"
    },
    {
      "ref": "tarunpaparaju/jigsaw-competition-part-of-speech-tagging",
      "title": "Jigsaw Competition : Part of Speech Tagging",
      "source": "live",
      "kernel_id": "3666553"
    },
    {
      "ref": "coolcoder22/colab-to-fine-tune-bert",
      "title": "colab to fine tune BERT",
      "source": "live",
      "kernel_id": "3666438"
    },
    {
      "ref": "abimannan/jigsaw-text-classify",
      "title": "Jigsaw Text classify",
      "source": "live",
      "kernel_id": "3660213"
    },
    {
      "ref": "matsumotoshintaro/kernel0cc2a9145d",
      "title": "kernel0cc2a9145d",
      "source": "live",
      "kernel_id": "3660037"
    },
    {
      "ref": "mvpvalues/4-outputs-no-rounding",
      "title": "4 outputs, no rounding",
      "source": "live",
      "kernel_id": "3655495"
    },
    {
      "ref": "bminixhofer/speed-up-your-rnn-with-sequence-bucketing",
      "title": "Speed up your RNN with Sequence Bucketing",
      "source": "live",
      "kernel_id": "3654211"
    },
    {
      "ref": "al1020964/toxicity-competition",
      "title": "Toxicity Competition",
      "source": "live",
      "kernel_id": "3653578"
    },
    {
      "ref": "maxl28618/toxic-comments-baseline-model",
      "title": "Toxic comments - Baseline model",
      "source": "live",
      "kernel_id": "3651165"
    },
    {
      "ref": "dkalev/generate-embeddings-matrix",
      "title": "Generate embeddings matrix",
      "source": "live",
      "kernel_id": "3649497"
    },
    {
      "ref": "rx74tsns/tf-idf-vectorizer-and-logistic-regression",
      "title": "TF-IDF Vectorizer and Logistic Regression",
      "source": "live",
      "kernel_id": "3647730"
    },
    {
      "ref": "saurabhrathor/toxicity-check",
      "title": "toxicity_check",
      "source": "live",
      "kernel_id": "3643285"
    },
    {
      "ref": "fnugget/eda-comment-lengths-and-punctuation-emoji-use",
      "title": "EDA - Comment Lengths and Punctuation/Emoji Use",
      "source": "live",
      "kernel_id": "3642534"
    },
    {
      "ref": "quincyqiang/01-tfidf-lr-0-89259",
      "title": "01-TFIDF-LR-0.89259",
      "source": "live",
      "kernel_id": "3642262"
    },
    {
      "ref": "julianoliveira/blend-the-blend",
      "title": "Blend the blend",
      "source": "live",
      "kernel_id": "3637086"
    },
    {
      "ref": "francoisdubois/add-a-gru-layer",
      "title": "Add a GRU layer",
      "source": "live",
      "kernel_id": "3635499"
    },
    {
      "ref": "krishanudb/data-exploration-and-simple-model-building",
      "title": "data exploration and simple model building",
      "source": "live",
      "kernel_id": "3634424"
    },
    {
      "ref": "coolcoder22/lightgbm-fast-compact-solution",
      "title": "LightGBM Fast Compact Solution",
      "source": "live",
      "kernel_id": "3634251"
    },
    {
      "ref": "francoisdubois/add-a-lstm-layer",
      "title": "Add a LSTM Layer",
      "source": "live",
      "kernel_id": "3633857"
    },
    {
      "ref": "jomaxx/jigsaw-toxicity-1-eda-of-tokens",
      "title": "Jigsaw Toxicity #1 (EDA of Tokens)",
      "source": "live",
      "kernel_id": "3632790"
    },
    {
      "ref": "elcaiseri/toxicity-bias-logistic-regression-tfidfvectorizer",
      "title": "Toxicity Bias Logistic Regression, TfidfVectorizer",
      "source": "live",
      "kernel_id": "3630539"
    },
    {
      "ref": "otaviocv/fast-logistic-regression",
      "title": "fast_logistic_regression",
      "source": "live",
      "kernel_id": "3630519"
    },
    {
      "ref": "authman/word-embedding-penalty",
      "title": "Word Embedding Penalty",
      "source": "live",
      "kernel_id": "3630130"
    },
    {
      "ref": "nholloway/insights-from-jigsaw-publications",
      "title": "Insights from Jigsaw Publications",
      "source": "live",
      "kernel_id": "3630041"
    },
    {
      "ref": "authman/simple-lstm-pytorch-with-batch-loading",
      "title": "Simple LSTM - PyTorch With Batch Loading",
      "source": "live",
      "kernel_id": "3629888"
    },
    {
      "ref": "matsuik/subgroup-negative-weighting",
      "title": "Subgroup negative weighting",
      "source": "live",
      "kernel_id": "3626642"
    },
    {
      "ref": "guillemkami/compact-simple-solution-gru-layers",
      "title": "Compact & Simple solution - GRU Layers",
      "source": "live",
      "kernel_id": "3624295"
    },
    {
      "ref": "rohankumar0002/jigsaw-nb",
      "title": "jigsaw_nb",
      "source": "live",
      "kernel_id": "3622611"
    },
    {
      "ref": "jingwhale/pre-process-data",
      "title": "pre-process data",
      "source": "live",
      "kernel_id": "3619435"
    },
    {
      "ref": "vladtaranchuk/124567",
      "title": "124567",
      "source": "live",
      "kernel_id": "3619102"
    },
    {
      "ref": "maxl28618/toxic-comments-eda",
      "title": "Toxic comments - EDA",
      "source": "live",
      "kernel_id": "3618996"
    },
    {
      "ref": "francoisdubois/build-an-embedding-based-on-fasttext",
      "title": "Build an embedding based on FastText",
      "source": "live",
      "kernel_id": "3615338"
    },
    {
      "ref": "matsuik/pytorch-pretrained-bert-from-source-in-dataset",
      "title": "pytorch-pretrained-BERT from source in dataset",
      "source": "live",
      "kernel_id": "3614862"
    },
    {
      "ref": "francoisdubois/build-a-word-embedding-with-glove-matrix",
      "title": "Build a word embedding with GloVe matrix",
      "source": "live",
      "kernel_id": "3612557"
    },
    {
      "ref": "christofhenkel/bert-embeddings-lstm",
      "title": "BERT-Embeddings + LSTM",
      "source": "live",
      "kernel_id": "3611078"
    },
    {
      "ref": "labdmitriy/jigsaw-linearsvc-tfidf-nb-features",
      "title": "Jigsaw - LinearSVC + Tfidf + NB features",
      "source": "live",
      "kernel_id": "3609334"
    },
    {
      "ref": "warcontroll/kernel0dde1bc223",
      "title": "kernel0dde1bc223",
      "source": "live",
      "kernel_id": "3609108"
    },
    {
      "ref": "gpreda/jigsaw-eda",
      "title": "Jigsaw EDA",
      "source": "live",
      "kernel_id": "3608940"
    },
    {
      "ref": "adarsh415/jigsaw-classification-problem",
      "title": "jigsaw classification problem",
      "source": "live",
      "kernel_id": "3608905"
    },
    {
      "ref": "maxjeblick/keras-lstm-with-competition-metric-callback",
      "title": "keras lstm with competition metric callback",
      "source": "live",
      "kernel_id": "3602545"
    },
    {
      "ref": "evilpsycho42/pytorch-batch-dynamic-padding-sort-pack",
      "title": "Pytorch batch dynamic padding & sort & pack",
      "source": "live",
      "kernel_id": "3601829"
    },
    {
      "ref": "francoisdubois/build-your-word-embedding-from-scratch",
      "title": "Build your Word embedding from scratch",
      "source": "live",
      "kernel_id": "3600602"
    },
    {
      "ref": "samarthsarin/ensemble-network-with-keras-and-embeddings",
      "title": "Ensemble Network with Keras and Embeddings",
      "source": "live",
      "kernel_id": "3596493"
    },
    {
      "ref": "tyagit3/training-speed-bucketing-variable-len-padding",
      "title": "↑ training speed- Bucketing & Variable len padding",
      "source": "live",
      "kernel_id": "3595216"
    },
    {
      "ref": "kunwar31/pytorch-pad-sequences-per-batch",
      "title": "PyTorch Pad Sequences per batch",
      "source": "live",
      "kernel_id": "3591431"
    },
    {
      "ref": "shilowu/testsubmission",
      "title": "TestSubmission",
      "source": "live",
      "kernel_id": "3589807"
    },
    {
      "ref": "mvpvalues/jigsaw-unintended-bias-kernel",
      "title": "Jigsaw Unintended Bias Kernel",
      "source": "live",
      "kernel_id": "3588494"
    },
    {
      "ref": "vivaroma/simple-lstm-with-learn-rate-tuned",
      "title": "Simple LSTM with Learn Rate Tuned",
      "source": "live",
      "kernel_id": "3588345"
    },
    {
      "ref": "shilowu/bert-toxicityclassification2",
      "title": "Bert-ToxicityClassification2",
      "source": "live",
      "kernel_id": "3585510"
    },
    {
      "ref": "hamishdickson/train-w2v-gensim",
      "title": "train w2v gensim",
      "source": "live",
      "kernel_id": "3584033"
    },
    {
      "ref": "nikhilroxtomar/simple-keras-lstm",
      "title": "Simple Keras LSTM",
      "source": "live",
      "kernel_id": "3582751"
    },
    {
      "ref": "dimitreoliveira/toxicity-bias-extensive-eda-and-bi-lstm",
      "title": "Toxicity Bias - extensive EDA and Bi LSTM",
      "source": "live",
      "kernel_id": "3580777"
    },
    {
      "ref": "nholloway/the-effect-of-word-embeddings-on-bias",
      "title": "The Effect of Word Embeddings on Bias",
      "source": "live",
      "kernel_id": "3573706"
    },
    {
      "ref": "tyagit3/logistic-regression-with-tfidf-word-level",
      "title": "Logistic regression with TfIdf word level",
      "source": "live",
      "kernel_id": "3572804"
    },
    {
      "ref": "uysimty/simple-toxicity-classification",
      "title": "Simple Toxicity Classification",
      "source": "live",
      "kernel_id": "3570245"
    },
    {
      "ref": "dtprksh50/toxic-challenge-v2",
      "title": "toxic_challenge_v2",
      "source": "live",
      "kernel_id": "3567709"
    },
    {
      "ref": "taohoang/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "3566656"
    },
    {
      "ref": "iluxave/cnn-using-identity-parameters-solution",
      "title": "CNN using Identity Parameters Solution",
      "source": "live",
      "kernel_id": "3560170"
    },
    {
      "ref": "avis1102/lstm-pytorch-model",
      "title": "LSTM--pytorch model",
      "source": "live",
      "kernel_id": "3558084"
    },
    {
      "ref": "buntyshah/jigsaw-classification-lstm",
      "title": "Jigsaw Classification LSTM",
      "source": "live",
      "kernel_id": "3547377"
    },
    {
      "ref": "shishu1421/simple-lstm-with-identity-parameters-fastai",
      "title": "Simple LSTM with Identity Parameters - FastAI",
      "source": "live",
      "kernel_id": "3543397"
    },
    {
      "ref": "kunwar31/simple-lstm-with-identity-parameters-fastai",
      "title": "Simple LSTM with Identity Parameters - FastAI",
      "source": "live",
      "kernel_id": "3539218"
    },
    {
      "ref": "mrugankakarte/jigsaw-unintended-bias-playbook",
      "title": "Jigsaw unintended bias playbook",
      "source": "live",
      "kernel_id": "3535133"
    },
    {
      "ref": "rohankumar0002/using-gensim-and-keras-lstm",
      "title": "using gensim and keras lstm",
      "source": "live",
      "kernel_id": "3534141"
    },
    {
      "ref": "kunwar31/simple-lstm-fastai",
      "title": "Simple LSTM - FastAI",
      "source": "live",
      "kernel_id": "3533248"
    },
    {
      "ref": "ashukr/naive-bayes",
      "title": "Naive-bayes ",
      "source": "live",
      "kernel_id": "3532196"
    },
    {
      "ref": "tanreinama/simple-lstm-using-identity-parameters-solution",
      "title": "Simple LSTM using Identity Parameters Solution",
      "source": "live",
      "kernel_id": "3531690"
    },
    {
      "ref": "cttsai/jigsaw-fast-compact-solution-with-gru",
      "title": "Jigsaw Fast Compact Solution with GRU",
      "source": "live",
      "kernel_id": "3530401"
    },
    {
      "ref": "httpwwwfszyc/bert-keras-with-warmup-and-excluding-wd-parameters",
      "title": "bert keras with warmup and excluding wd parameters",
      "source": "live",
      "kernel_id": "3525138"
    },
    {
      "ref": "dnik007/jigsaw-challenge-data-pre-processing-and-keras",
      "title": "Jigsaw Challenge: Data Pre processing and Keras",
      "source": "live",
      "kernel_id": "3524962"
    },
    {
      "ref": "danofer/jigsaw-bias-joint-protected-categories",
      "title": "Jigsaw Bias - Joint protected categories",
      "source": "live",
      "kernel_id": "3523917"
    },
    {
      "ref": "sorzhe/pytorch-toxic-detection-with-callbacks",
      "title": "Pytorch toxic detection with Callbacks",
      "source": "live",
      "kernel_id": "3523263"
    },
    {
      "ref": "bminixhofer/simple-lstm-pytorch-version",
      "title": "Simple LSTM - PyTorch version",
      "source": "live",
      "kernel_id": "3522342"
    },
    {
      "ref": "hamishdickson/previous-competition-data-match",
      "title": "Previous competition data match",
      "source": "live",
      "kernel_id": "3518652"
    },
    {
      "ref": "tatianass/jigsaw-dataframe-with-new-categories",
      "title": "Jigsaw - Dataframe with new categories",
      "source": "live",
      "kernel_id": "3518432"
    },
    {
      "ref": "taindow/bert-a-fine-tuning-example",
      "title": "BERT: a fine tuning example",
      "source": "live",
      "kernel_id": "3518006"
    },
    {
      "ref": "antondergunov/basic-exploratory-analysis",
      "title": "Basic exploratory analysis",
      "source": "live",
      "kernel_id": "3515969"
    },
    {
      "ref": "xffjlg/wrap-submetricsauc-class",
      "title": "Wrap SubmetricsAUC class",
      "source": "live",
      "kernel_id": "3515886"
    },
    {
      "ref": "aming9527/embed-lstm-attention",
      "title": "embed+LSTM+attention",
      "source": "live",
      "kernel_id": "3515740"
    },
    {
      "ref": "bkkaggle/allennlp-starter-kit",
      "title": "AllenNLP Starter Kit",
      "source": "live",
      "kernel_id": "3509373"
    },
    {
      "ref": "nikhilsharma00/clean-data-keras-embbedings-cudnn-predict",
      "title": "Clean Data>Keras Embbedings>CuDNN>Predict",
      "source": "live",
      "kernel_id": "3508823"
    },
    {
      "ref": "sergeykalutsky/augmenting-and-parsing-more-data",
      "title": "Augmenting and parsing more data",
      "source": "live",
      "kernel_id": "3507278"
    },
    {
      "ref": "ajaykgp12/can-model-learn-its-word-embeddings-keras-and-gru",
      "title": "Can Model Learn its word Embeddings? Keras and GRU",
      "source": "live",
      "kernel_id": "3504969"
    },
    {
      "ref": "elias8888/bert-baseline-score-0-91",
      "title": "BERT-Baseline-Score-0.91",
      "source": "live",
      "kernel_id": "3502601"
    },
    {
      "ref": "swarnim97/jigsaw-toxicity-using-cnn1d-and-cudnnlstm",
      "title": "Jigsaw Toxicity Using CNN1D and CuDNNLSTM",
      "source": "live",
      "kernel_id": "3501948"
    },
    {
      "ref": "nz0722/simple-eda-text-preprocessing-jigsaw",
      "title": "Simple EDA Text Preprocessing - Jigsaw ",
      "source": "live",
      "kernel_id": "3499080"
    },
    {
      "ref": "abhigupta4981/pytorch-train-with-callbacks",
      "title": "Pytorch train with Callbacks",
      "source": "live",
      "kernel_id": "3498799"
    },
    {
      "ref": "tarunpaparaju/jigsaw-competition-eda-and-modeling",
      "title": "Jigsaw Competition : EDA and Modeling",
      "source": "live",
      "kernel_id": "3495165"
    },
    {
      "ref": "adityaecdrid/public-version-text-cleaning-vocab-65",
      "title": "[Public Version] Text Cleaning - Vocab ~65%+",
      "source": "live",
      "kernel_id": "3494330"
    },
    {
      "ref": "aming9527/kernel-pytorch-base-model-cp",
      "title": "kernel-PyTorch base model cp",
      "source": "live",
      "kernel_id": "3493534"
    },
    {
      "ref": "pedrormarques/jigsaw-gru-classes",
      "title": "jigsaw-gru-classes",
      "source": "live",
      "kernel_id": "3488980"
    },
    {
      "ref": "coolcoder22/simple-logisticregression",
      "title": "Simple LogisticRegression",
      "source": "live",
      "kernel_id": "3487596"
    },
    {
      "ref": "hung96ad/gru-lstm",
      "title": "GRU+LSTM",
      "source": "live",
      "kernel_id": "3485750"
    },
    {
      "ref": "jkfirst/jigsaw-submission",
      "title": "jigsaw submission",
      "source": "live",
      "kernel_id": "3485062"
    },
    {
      "ref": "matthew886/jigsaw-fast-compact-solution",
      "title": "Jigsaw Fast Compact Solution",
      "source": "live",
      "kernel_id": "3482358"
    },
    {
      "ref": "muonneutrino/lightgbm-starter-kernel",
      "title": "LightGBM Starter Kernel",
      "source": "live",
      "kernel_id": "3481591"
    },
    {
      "ref": "cevangelist/a-little-more-detailed-eda-and-simple-lstm",
      "title": "A little more detailed EDA and simple LSTM",
      "source": "live",
      "kernel_id": "3481137"
    },
    {
      "ref": "takafumif/simple-lgbm",
      "title": "Simple LGBM",
      "source": "live",
      "kernel_id": "3480384"
    },
    {
      "ref": "bkkaggle/jigsaw-allennlp",
      "title": "Jigsaw Allennlp",
      "source": "live",
      "kernel_id": "3480321"
    },
    {
      "ref": "thousandvoices/simple-lstm",
      "title": "Simple LSTM",
      "source": "live",
      "kernel_id": "3478400"
    },
    {
      "ref": "powercode/bilstm-gru-caps",
      "title": "bilstm+gru+caps",
      "source": "live",
      "kernel_id": "3476485"
    },
    {
      "ref": "rolikasi/keras-lstm",
      "title": "keras lstm",
      "source": "live",
      "kernel_id": "3473583"
    },
    {
      "ref": "stanislavblinov/sweet-bi-lstm-attentionwithcontext",
      "title": "Sweet Bi_LSTM + AttentionWithContext ",
      "source": "live",
      "kernel_id": "3473051"
    },
    {
      "ref": "gpreda/jigsaw-fast-compact-solution",
      "title": "Jigsaw Fast Compact Solution",
      "source": "live",
      "kernel_id": "3473035"
    },
    {
      "ref": "anubhav1302/j-toxicity-code",
      "title": "J_Toxicity_code",
      "source": "live",
      "kernel_id": "3471634"
    },
    {
      "ref": "harsh306/keval1",
      "title": "keval1",
      "source": "live",
      "kernel_id": "3471301"
    },
    {
      "ref": "ichabuddaeta/fun-times-with-r-and-toxicity",
      "title": "Fun times with R and Toxicity",
      "source": "live",
      "kernel_id": "3471284"
    },
    {
      "ref": "chakkarapani/kernel-chakra-toxicity",
      "title": "kernel-chakra-toxicity",
      "source": "live",
      "kernel_id": "3470812"
    },
    {
      "ref": "alber8295/nb-svm-linear-baseline",
      "title": "NB-SVM linear baseline",
      "source": "live",
      "kernel_id": "3465673"
    },
    {
      "ref": "mohanamurali/bgow-tf-idf-lr-w2v-lgb-bayesopt",
      "title": "bgow +Tf-Idf  + lR &  W2V+ Lgb + BayesOpt",
      "source": "live",
      "kernel_id": "3464232"
    },
    {
      "ref": "sergeykalutsky/searching-for-balance",
      "title": "Searching for Balance",
      "source": "live",
      "kernel_id": "3463716"
    },
    {
      "ref": "prabanch/jigsaw-unintended-bias-in-toxicity-classification",
      "title": "Jigsaw Unintended Bias in Toxicity Classification",
      "source": "live",
      "kernel_id": "3463675"
    },
    {
      "ref": "beloruk1/comparing-embeddings",
      "title": "Comparing embeddings",
      "source": "live",
      "kernel_id": "3463173"
    },
    {
      "ref": "sakami/pytorch-base-model",
      "title": "PyTorch base model",
      "source": "live",
      "kernel_id": "3462474"
    },
    {
      "ref": "ashukr/curating-a-subset",
      "title": "curating a subset",
      "source": "live",
      "kernel_id": "3461601"
    },
    {
      "ref": "shakespere/keras-baseline-lstm-att-5-fold-bn-dp-2embedding-l",
      "title": "keras baseline lstm+att+5-fold BN DP+2embedding+L",
      "source": "live",
      "kernel_id": "3460617"
    },
    {
      "ref": "plasticgrammer/jigsaw-toxicity-classification-playground",
      "title": "Jigsaw Toxicity Classification: playground",
      "source": "live",
      "kernel_id": "3460027"
    },
    {
      "ref": "suryamr/toxic-comments-classifier-random-forest-acc-100",
      "title": "toxic comments  classifier random forest acc 100%",
      "source": "live",
      "kernel_id": "3457631"
    },
    {
      "ref": "sandeepkumar121995/keras-bi-gru-lstm-attention-fasttext",
      "title": "Keras Bi-GRU-LSTM-Attention-Fasttext",
      "source": "live",
      "kernel_id": "3456137"
    },
    {
      "ref": "georsara1/reducing-bias-not-all-spicy-words-are-toxic",
      "title": "Reducing bias: Not all 'spicy' words are Toxic",
      "source": "live",
      "kernel_id": "3456021"
    },
    {
      "ref": "sergeykalutsky/pytorch-starter",
      "title": "PyTorch Starter",
      "source": "live",
      "kernel_id": "3454849"
    },
    {
      "ref": "christofhenkel/ulmfit-fast-ai-starter",
      "title": "ULMFit (fast.ai) starter",
      "source": "live",
      "kernel_id": "3450916"
    },
    {
      "ref": "acstream/multilayer-cudnnlstm-cudnngru",
      "title": "MultiLayer CuDNNLSTM + CuDNNGRU ",
      "source": "live",
      "kernel_id": "3447450"
    },
    {
      "ref": "nevermoi/jigsaw-toxic-prediction-by-simple-linearsvr-tfidf",
      "title": "jigsaw-toxic-prediction-by-simple-linearsvr-tfidf",
      "source": "live",
      "kernel_id": "3446051"
    },
    {
      "ref": "lsjsj92/toxic-simple-eda-and-modeling-with-lstm",
      "title": "toxic simple EDA and modeling with LSTM",
      "source": "live",
      "kernel_id": "3446033"
    },
    {
      "ref": "christofhenkel/keras-baseline-lstm-attention-5-fold",
      "title": "keras baseline lstm + attention 5-fold",
      "source": "live",
      "kernel_id": "3444639"
    },
    {
      "ref": "christofhenkel/loading-bert-using-pytorch-with-tokenizer-apex",
      "title": "Loading BERT using pytorch (with tokenizer & apex)",
      "source": "live",
      "kernel_id": "3443636"
    },
    {
      "ref": "masterscrat/lsa-lgbm-baseline-w-system-monitoring",
      "title": "LSA, LGBM Baseline w/ System Monitoring",
      "source": "live",
      "kernel_id": "3441287"
    },
    {
      "ref": "tp2422/jigsaw-v1",
      "title": "Jigsaw - v1",
      "source": "live",
      "kernel_id": "3439482"
    },
    {
      "ref": "chewzy/eda-toxicity-of-identities-updated-29-4",
      "title": "EDA - Toxicity of Identities (Updated 29/4)",
      "source": "live",
      "kernel_id": "3439283"
    },
    {
      "ref": "adityaecdrid/regex-primer-annoying-artgor-xd",
      "title": "Regex Primer + Annoying Artgor xD :)",
      "source": "live",
      "kernel_id": "3438651"
    },
    {
      "ref": "taindow/simple-cudnngru-python-keras",
      "title": "Simple CuDNNGRU [Python + Keras]",
      "source": "live",
      "kernel_id": "3438141"
    },
    {
      "ref": "leighplt/pytorch-torchtext-glove",
      "title": "PyTorch, TorchText, Glove",
      "source": "live",
      "kernel_id": "3438091"
    },
    {
      "ref": "rahulvks/lstm-attention-keras",
      "title": "LSTM  Attention Keras",
      "source": "live",
      "kernel_id": "3437424"
    },
    {
      "ref": "felipemello/there-is-no-medal-without-eda-comment-s-toxicity",
      "title": "There is no mEDAl without EDA - Comment's toxicity",
      "source": "live",
      "kernel_id": "3437172"
    },
    {
      "ref": "gsreyan/simple-exploration-notebook",
      "title": "Simple Exploration Notebook",
      "source": "live",
      "kernel_id": "3435566"
    },
    {
      "ref": "justjun0321/simple-sklearn-models",
      "title": "Simple Sklearn models",
      "source": "live",
      "kernel_id": "3433791"
    },
    {
      "ref": "jazivxt/ontological-paradox-civil-bias",
      "title": "Ontological Paradox Civil Bias",
      "source": "live",
      "kernel_id": "3429371"
    },
    {
      "ref": "artgor/cnn-in-keras-on-folds",
      "title": "CNN in keras on folds",
      "source": "live",
      "kernel_id": "3428090"
    },
    {
      "ref": "artgor/toxicity-eda-logreg-and-nn-interpretation",
      "title": "Toxicity EDA, logreg and NN interpretation",
      "source": "live",
      "kernel_id": "3428089"
    },
    {
      "ref": "artgor/comparing-architectures-and-embeddings",
      "title": "Comparing architectures and embeddings",
      "source": "live",
      "kernel_id": "3427871"
    },
    {
      "ref": "dborkan/benchmark-kernel",
      "title": "Benchmark Kernel",
      "source": "live",
      "kernel_id": "3413278"
    },
    {
      "ref": "mlwhiz/parallelization-kernel",
      "title": "",
      "source": "meta",
      "kernel_id": "3769255"
    },
    {
      "ref": "suchith0312/pytorch-dataloader-testing",
      "title": "",
      "source": "meta",
      "kernel_id": "3962529"
    },
    {
      "ref": "guiyihan/text-classification",
      "title": "",
      "source": "meta",
      "kernel_id": "3975631"
    },
    {
      "ref": "soulmachine/jigsaw-utils-kaggle",
      "title": "",
      "source": "meta",
      "kernel_id": "4494654"
    },
    {
      "ref": "t4tapasroy/kernel6f7658cce3",
      "title": "",
      "source": "meta",
      "kernel_id": "4370809"
    },
    {
      "ref": "isikkuntay/bert-and-bidaf",
      "title": "",
      "source": "meta",
      "kernel_id": "6963276"
    },
    {
      "ref": "alincijov/nlp-starter-continuous-bag-of-words-cbow",
      "title": "",
      "source": "meta",
      "kernel_id": "9415350"
    },
    {
      "ref": "alexisbcook/exercise-identifying-bias-in-ai",
      "title": "",
      "source": "meta",
      "kernel_id": "15622654"
    },
    {
      "ref": "nancyhassantaya/finalbert",
      "title": "",
      "source": "meta",
      "kernel_id": "17951020"
    },
    {
      "ref": "kroha5/toxicity-logreg",
      "title": "",
      "source": "meta",
      "kernel_id": "18483514"
    },
    {
      "ref": "aamartesu/ai4code-train-tfrankencoder",
      "title": "",
      "source": "meta",
      "kernel_id": "18840308"
    },
    {
      "ref": "get2jawa/nlp-basic-eda-cleaning-lstm-lb-0-79",
      "title": "",
      "source": "meta",
      "kernel_id": "22076659"
    },
    {
      "ref": "mst8823/roberta-base-with-jigsaw-toxic-comment-infer",
      "title": "",
      "source": "meta",
      "kernel_id": "22080361"
    },
    {
      "ref": "mst8823/roberta-base-with-jigsaw-toxic-comment-train",
      "title": "",
      "source": "meta",
      "kernel_id": "22080309"
    },
    {
      "ref": "taoufikelkhaouja/toxic-comments-bert",
      "title": "",
      "source": "meta",
      "kernel_id": "22491902"
    },
    {
      "ref": "huntergregory/ranking-toxicity-of-wikipedia-comments",
      "title": "",
      "source": "meta",
      "kernel_id": "22601516"
    },
    {
      "ref": "masatomurakawamm/jigsaw-tftransformers-regressor-with-attention",
      "title": "",
      "source": "meta",
      "kernel_id": "22526189"
    },
    {
      "ref": "zsofislosar/my-first-submission",
      "title": "",
      "source": "meta",
      "kernel_id": "22437217"
    },
    {
      "ref": "mfsher/mxfsher-kaggle-competition",
      "title": "",
      "source": "meta",
      "kernel_id": "24561967"
    },
    {
      "ref": "shaleenkalsi/bi-lstm-for-ner",
      "title": "",
      "source": "meta",
      "kernel_id": "28399331"
    },
    {
      "ref": "akshatpattiwar/leaf-detection-classification",
      "title": "",
      "source": "meta",
      "kernel_id": "30301570"
    },
    {
      "ref": "mayingning/assignment3",
      "title": "",
      "source": "meta",
      "kernel_id": "33361552"
    },
    {
      "ref": "l048596/sarcasm-bert-tensorflow-79-39",
      "title": "",
      "source": "meta",
      "kernel_id": "41746811"
    },
    {
      "ref": "sajudhamza/project",
      "title": "",
      "source": "meta",
      "kernel_id": "47812179"
    },
    {
      "ref": "hodinhtrieu/keras-baseline-lstm-attention-5-fold",
      "title": "",
      "source": "meta",
      "kernel_id": "54330362"
    },
    {
      "ref": "alexanderkireev/04-ml-trainings-nlp",
      "title": "",
      "source": "meta",
      "kernel_id": "70487269"
    },
    {
      "ref": "kienmaitrung/datacrawlingtesting",
      "title": "",
      "source": "meta",
      "kernel_id": "78337399"
    },
    {
      "ref": "jazivxt/silence-of-the-sheeps-the-antisheple-puzzle",
      "title": "",
      "source": "meta",
      "kernel_id": "87815258"
    },
    {
      "ref": "sudhikshavalluru/notebookc87fedac39",
      "title": "",
      "source": "meta",
      "kernel_id": "113343152"
    }
  ],
  "errors": []
}