{ "total": 862, "topics": [ { "id": 175313, "title": "Congratulations: With/Without Context Special Prize Winners!", "comment_count": 12, "views": 0, "votes": 6, "reused": true }, { "id": 154271, "title": "Welcome!", "comment_count": 34, "views": 0, "votes": 15, "reused": true }, { "id": 161943, "title": "True duplicates in this dataset", "comment_count": 19, "views": 0, "votes": 65, "reused": true }, { "id": 173639, "title": "Thank you Kagglers - 1st Place Datasets, 1st Notebooks, 1st Discussions", "comment_count": 360, "views": 0, "votes": 840, "reused": true }, { "id": 165653, "title": "For AUC Metric, Ensemble using Power Averaging", "comment_count": 20, "views": 0, "votes": 114, "reused": true }, { "id": 160147, "title": "CNN Input Size Explained", "comment_count": 200, "views": 0, "votes": 508, "reused": true }, { "id": 175633, "title": "3rd place solution overview", "comment_count": 42, "views": 0, "votes": 122, "reused": true }, { "id": 171726, "title": "1st Bangladeshi Notebook GrandMaster", "comment_count": 76, "views": 0, "votes": 87, "reused": true }, { "id": 165526, "title": "Triple Stratified Leak-Free KFold CV", "comment_count": 149, "views": 0, "votes": 384, "reused": true }, { "id": 175412, "title": "1st place solution", "comment_count": 151, "views": 0, "votes": 384, "reused": true }, { "id": 175614, "title": "How To CV and How To Ensemble OOF Files", "comment_count": 89, "views": 0, "votes": 360, "reused": true }, { "id": 175846, "title": " Justification and 4th place Solution Overview", "comment_count": 14, "views": 0, "votes": 21, "reused": true }, { "id": 175352, "title": "27th overview - 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2nd with context prize (edited)", "comment_count": 1, "views": 0, "votes": 34, "reused": true }, { "id": 181485, "title": "###my results for this Competition (SIIM-ISIC Melanoma Classification)###", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 174630, "title": "Date block Number", "comment_count": 7, "views": 0, "votes": -8, "reused": true }, { "id": 179255, "title": "qst can any one tell me why im getting this problem with the f1 score ?????", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 175500, "title": "Ugly Duckling: Did Anything Work?", "comment_count": 1, "views": 0, "votes": 7, "reused": true }, { "id": 156966, "title": "Are you a TPU Star?", "comment_count": 3, "views": 0, "votes": 9, "reused": true }, { "id": 175369, "title": "Learnings of a First Time Participant", "comment_count": 11, "views": 0, "votes": 12, "reused": true }, { "id": 169139, "title": "How To Upsample Malignant - TFRecords - JPEGs ", "comment_count": 138, "views": 0, "votes": 185, "reused": true }, { "id": 164092, "title": "PyTorch JPEGs - 768, 512, 384, 256 - TensorFlow JPEGs", "comment_count": 76, "views": 0, "votes": 197, "reused": true }, { "id": 177924, "title": "40th Place Summary - In Chris and CV we trust", "comment_count": 3, "views": 0, "votes": 6, "reused": true }, { "id": 178213, "title": "Summary from different good solutions of SIIM ", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 176272, "title": "Any of the top teams used cloud only (free) resources ?", "comment_count": 19, "views": 0, "votes": 6, "reused": true }, { "id": 176484, "title": "1868th place in 1st competition! ", "comment_count": 1, "views": 0, "votes": -12, "reused": true }, { "id": 177818, "title": "Cutmix in Tensorflow 2.x", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 177795, "title": "Leaderboard still changing ?!", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 175156, "title": "Evidence regarding private sharing", "comment_count": 264, "views": 0, "votes": 341, "reused": true }, { "id": 176930, "title": "For those who start image classification!", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175765, "title": "12th place solution", "comment_count": 9, "views": 0, "votes": 11, "reused": true }, { "id": 176154, "title": "6th Place Write-Up", "comment_count": 10, "views": 0, "votes": 24, "reused": true }, { "id": 175655, "title": "85th description - random label smoothing", "comment_count": 5, "views": 0, "votes": 11, "reused": true }, { "id": 163478, "title": "HELP : Keyerror while enumerating over DataLoader outputs", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 175891, "title": "TF vs Pyorch mystery solved", "comment_count": 43, "views": 0, "votes": 29, "reused": true }, { "id": 175573, "title": "Won my First Solo Silver Medal", "comment_count": 33, "views": 0, "votes": 43, "reused": true }, { "id": 174635, "title": "Some weird phenomenon again.", "comment_count": 177, "views": 0, "votes": 123, "reused": true }, { "id": 177044, "title": "My PyTorch training code", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175781, "title": "Stacking on meta-data including Ensembling and Pseudo Labeling", "comment_count": 9, "views": 0, "votes": 11, "reused": true }, { "id": 154297, "title": "New to Machine Learning or Kaggle?", "comment_count": 62, "views": 0, "votes": 17, "reused": true }, { "id": 175486, "title": "157th place solution", "comment_count": 7, "views": 0, "votes": 6, "reused": true }, { "id": 175339, "title": "Did we lost $30,000, I can't believe my eyes", "comment_count": 14, "views": 0, "votes": 34, "reused": true }, { "id": 176807, "title": "Dataset Content", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 175391, "title": "12th Place unexpected result", "comment_count": 20, "views": 0, "votes": 52, "reused": true }, { "id": 176489, "title": "Learnings from a solo silver medalist entering in the last 2 weeks", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 156176, "title": "Enjoyable, informative but frustrating at times.", "comment_count": 13, "views": 0, "votes": 23, "reused": true }, { "id": 176382, "title": "Report of 408 submissions!", "comment_count": 21, "views": 0, "votes": 23, "reused": true }, { "id": 176088, "title": "Every heartbreak will be a lesson", "comment_count": 6, "views": 0, "votes": 14, "reused": true }, { "id": 175618, "title": "Our best private solution (0.9498) [not selected]", "comment_count": 5, "views": 0, "votes": 23, "reused": true }, { "id": 175559, "title": "LB probing: our insights into the test data", "comment_count": 7, "views": 0, "votes": 38, "reused": true }, { "id": 176511, "title": "Explanation of Our 8TTA (get_trans)", "comment_count": 1, "views": 0, "votes": 18, "reused": true }, { "id": 175504, "title": "1st Place Solution Code (Small ver.) Released!", "comment_count": 16, "views": 0, "votes": 50, "reused": true }, { "id": 176406, "title": "What worked in this competition", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 176338, "title": "24th place solution and my way to get it ", "comment_count": 11, "views": 0, "votes": 18, "reused": true }, { "id": 175155, "title": "TPU | Google SDK connect issue | Keeps on loading", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174865, "title": "Early Stopping observations", "comment_count": 12, "views": 0, "votes": 1, "reused": true }, { "id": 175396, "title": "what to do after competition?", "comment_count": 6, "views": 0, "votes": 13, "reused": true }, { "id": 176270, "title": "Unsupervised Detection and Stacking (10th Public / 101st Private) (Kha Vo's view)", "comment_count": 7, "views": 0, "votes": 16, "reused": true }, { "id": 175334, "title": "241st place (bronze) solution (+ GitHub) with batch sampling", "comment_count": 18, "views": 0, "votes": 21, "reused": true }, { "id": 175628, "title": "The full list of bots on the LB", "comment_count": 7, "views": 0, "votes": 18, "reused": true }, { "id": 175329, "title": "Missed Opportunity - 4th place - Solo Gold ", "comment_count": 21, "views": 0, "votes": 9, "reused": true }, { "id": 175594, "title": "Clean out has begun???", "comment_count": 28, "views": 0, "votes": 26, "reused": true }, { "id": 175575, "title": "7th Place Solution(Short ver.)", "comment_count": 10, "views": 0, "votes": 18, "reused": true }, { "id": 175318, "title": "I said it: high score public kernels are dangerous", "comment_count": 32, "views": 0, "votes": 33, "reused": true }, { "id": 175410, "title": "24th Place Solution", "comment_count": 14, "views": 0, "votes": 25, "reused": true }, { "id": 175312, "title": "Private Leaderboard FINAL", "comment_count": 33, "views": 0, "votes": 53, "reused": true }, { "id": 175854, "title": "Will A Team Submission and Team be Removed if a member profile has been deleted ", "comment_count": 19, "views": 0, "votes": -8, "reused": true }, { "id": 176191, "title": "The final Leaderboard has been published", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175409, "title": "I didn't choose a 0.939 submission :( ", "comment_count": 9, "views": 0, "votes": 8, "reused": true }, { "id": 175394, "title": "CV is all you need!!! 1044 Public to 75 Private (0.953 CV)", "comment_count": 5, "views": 0, "votes": 17, "reused": true }, { "id": 175354, "title": "Public Kernels Ensemble. ", "comment_count": 27, "views": 0, "votes": 16, "reused": true }, { "id": 175365, "title": "Kagglers acting like overfitting hyperparameter search", "comment_count": 7, "views": 0, "votes": 12, "reused": true }, { "id": 176192, "title": "Top 100 CSV files", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 175538, "title": "[Summary] Public 11 Private 23 and Congrats to a new Master", "comment_count": 8, "views": 0, "votes": 30, "reused": true }, { "id": 176085, "title": "SIIM 2020 vs SIIM 2019", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 175825, "title": "1st Place Best Model & Inference Code Released!", "comment_count": 2, "views": 0, "votes": 26, "reused": true }, { "id": 175721, "title": "254th Place Solution", "comment_count": 5, "views": 0, "votes": 18, "reused": true }, { "id": 175595, "title": "What was the point?", "comment_count": 14, "views": 0, "votes": 31, "reused": true }, { "id": 175449, "title": "Did MinMax ensemble work?", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 175493, "title": "What a shake up !", "comment_count": 2, "views": 0, "votes": 26, "reused": true }, { "id": 175587, "title": "LB gets cleaned up?", "comment_count": 5, "views": 0, "votes": 9, "reused": true }, { "id": 176052, "title": " Colab Pro available outside US?", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 176042, "title": "Test efs fsefes fdsf sdf sdf sd", "comment_count": 0, "views": 0, "votes": -18 }, { "id": 175466, "title": "For what it's worth: 10 public / 101 private (silver)", "comment_count": 19, "views": 0, "votes": 39, "reused": true }, { "id": 175418, "title": "Pseudo labelling: What worked and what didn't?", "comment_count": 4, "views": 0, "votes": 11, "reused": true }, { "id": 175656, "title": "I chose wrongly !!!, I had 12 submissions in the medal zone", "comment_count": 14, "views": 0, "votes": null, "reused": true }, { "id": 175440, "title": "Thanks Chris Deotte!!!", "comment_count": 2, "views": 0, "votes": 20, "reused": true }, { "id": 175729, "title": "Not a ground-breaking idea, just one way to keep track of experiments.", "comment_count": 15, "views": 0, "votes": 14, "reused": true }, { "id": 175769, "title": "Structured Chaos - Some Organizational Tips", "comment_count": 7, "views": 0, "votes": 8, "reused": true }, { "id": 175893, "title": "Dataset Citation", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 175467, "title": "With Patient context", "comment_count": 10, "views": 0, "votes": 5, "reused": true }, { "id": 175333, "title": "Great ShakeUp And Variation ", "comment_count": 9, "views": 0, "votes": 2, "reused": true }, { "id": 175366, "title": "Our CV 0.95999 Ensemble Wins!", "comment_count": 18, "views": 0, "votes": 68, "reused": true }, { "id": 167551, "title": "View Images with RAPIDS cuML TSNE", "comment_count": 45, "views": 0, "votes": 136, "reused": true }, { "id": 175362, "title": "Congratulations x2 to Ajibesh Mohapatra", "comment_count": 30, "views": 0, "votes": 72, "reused": true }, { "id": 175744, "title": "176th Place Write-up", "comment_count": 4, "views": 0, "votes": 11, "reused": true }, { "id": 175448, "title": "I failed to choose the best one but I've learned!", "comment_count": 19, "views": 0, "votes": 14, "reused": true }, { "id": 175400, "title": "Is SIIM-ISIC a kind of M5 bis ?", "comment_count": 2, "views": 0, "votes": 7, "reused": true }, { "id": 173863, "title": "Annoying score on Leaderboard", "comment_count": 35, "views": 0, "votes": 11, "reused": true }, { "id": 166316, "title": "ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float).", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175560, "title": "GNN for Ugly Duckling Effect ?", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 175521, "title": "Just a reminder of removal all the suspects.", "comment_count": 6, "views": 0, "votes": 20, "reused": true }, { "id": 175196, "title": "First of all, my account is actually advertised by the screenshots of angtk", "comment_count": 8, "views": 0, "votes": -38, "reused": true }, { "id": 175205, "title": "my account is actually advertised by the screenshots of angtk", "comment_count": 29, "views": 0, "votes": -79, "reused": true }, { "id": 175675, "title": "Error code 404 ", "comment_count": 1, "views": 0, "votes": -1, "reused": true }, { "id": 175338, "title": "A tribute to Sir Chris Deotte", "comment_count": 16, "views": 0, "votes": 62, "reused": true }, { "id": 175386, "title": "Iterating faster by careful sampling (157th private)", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 175346, "title": "Context Specific Submissions thread", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 175402, "title": "Pytorch(Stratified-Kfold-5fold - 256*256) - No Augmentation - No Triple Stratified - No Multiple resized images -Public LB- 91.4 Private LB Score- 90.41", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 175425, "title": "From 66x online tutorials to winning the First Provisional Silver Medal", "comment_count": 8, "views": 0, "votes": 12, "reused": true }, { "id": 175331, "title": "0.9500 Any touched? ", "comment_count": 8, "views": 0, "votes": 18, "reused": true }, { "id": 175023, "title": "Good Luck Everyone!", "comment_count": 42, "views": 0, "votes": 46, "reused": true }, { "id": 175380, "title": "Shaked to the core", "comment_count": 7, "views": 0, "votes": 4, "reused": true }, { "id": 175579, "title": "Should it be allowed to create blends using others's submission.csv's?", "comment_count": 2, "views": 0, "votes": 5, "reused": true }, { "id": 175514, "title": "What's the diagnosis unknown mean?", "comment_count": 5, "views": 0, "votes": 6, "reused": true }, { "id": 175461, "title": "Winners have made my belief in Pytorch even stronger", "comment_count": 14, "views": 0, "votes": 5, "reused": true }, { "id": 175066, "title": "Issue with PyTorch XLA.", "comment_count": 15, "views": 0, "votes": 5, "reused": true }, { "id": 173130, "title": "Upsampling Malignant Improves AUC 0.003!", "comment_count": 34, "views": 0, "votes": 53, "reused": true }, { "id": 174469, "title": "Shake-up like M5 forecasting? ", "comment_count": 38, "views": 0, "votes": 9, "reused": true }, { "id": 175379, "title": "still interested to know : 0.99 on public LB, how is it done?", "comment_count": 8, "views": 0, "votes": 14, "reused": true }, { "id": 175372, "title": "Hacking super-resolution images", "comment_count": 13, "views": 0, "votes": 6, "reused": true }, { "id": 175385, "title": "When is it okay to publish high scoring kernels?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175319, "title": "Was fun ....", "comment_count": 4, "views": 0, "votes": 12, "reused": true }, { "id": 175376, "title": "Jump in the Private LB", "comment_count": 1, "views": 0, "votes": -8, "reused": true }, { "id": 175475, "title": "139th Place Summary", "comment_count": 2, "views": 0, "votes": 12, "reused": true }, { "id": 175473, "title": "Have anyone noticed some users have double accounts in LB? ", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 175295, "title": "Lots of Heat on LB", "comment_count": 23, "views": 0, "votes": 37, "reused": true }, { "id": 175039, "title": "Brainstorm of Ideas Kaggle could do to prevent / reduce fraud", "comment_count": 7, "views": 0, "votes": 4, "reused": true }, { "id": 175427, "title": "Choose the wrong csv paid the price : didn't choose 0.9430", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 175315, "title": "The shakeup is really unbelievable!", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 175421, "title": "Out of Top 100 Rankings - Only 7 teams rank decreased (Is this a surprise?)", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 175390, "title": "Did we start ensembling too early?", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 175327, "title": "Who had the highest PyTorch Single Model score on Private LB?", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 175422, "title": "My Approach and lesson learned!", "comment_count": 0, "views": 0, "votes": 7 }, { "id": 175201, "title": "First of all, my account is actually advertised by the screenshots of angtk", "comment_count": 16, "views": 0, "votes": -45, "reused": true }, { "id": 175351, "title": "302th Solution Writeup - Always trust your CV", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 175181, "title": "ROC of OOF Predicitions (Model Effnet)", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 175395, "title": "Diversification is the key!", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 174852, "title": "High score notebooks reminder", "comment_count": 6, "views": 0, "votes": 7, "reused": true }, { "id": 175314, "title": "\"In CV we trust\" should be in researchers's anthem", "comment_count": 9, "views": 0, "votes": 12, "reused": true }, { "id": 175387, "title": "a note on giving online lesson using kaggle", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 174920, "title": "Where is the warning banner for notebooks?", "comment_count": 44, "views": 0, "votes": 44, "reused": true }, { "id": 175382, "title": "Blend simple tabular model can improve PB score", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 175328, "title": " Congratulations 🎊 to winners", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 175347, "title": "Any Papers or code links are possible for context specific research on melonama", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 175368, "title": "only stack the public kernel can reach the top 10", "comment_count": 0, "views": 0, "votes": -4 }, { "id": 175325, "title": "Shake up warning", "comment_count": 1, "views": 0, "votes": -1, "reused": true }, { "id": 175310, "title": "Shakeup was massive!", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 175353, "title": "Weighting metadata high seems to be not good idea!?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174483, "title": "Recommendations on Final submissions --Reduce overfitting??", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 175350, "title": "[Question] How do we check which of our 3 submissions performed the best?", "comment_count": 1, "views": 0, "votes": -1, "reused": true }, { "id": 168152, "title": "What's your best (single) Pytorch Model score ?", "comment_count": 111, "views": 0, "votes": 37, "reused": true }, { "id": 175341, "title": "CV / Private LB score", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175349, "title": "Who would have known about the shakeup? Everyone! (Public - 153 rank, Private - 41 rank)", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175332, "title": "This Supposed to be my Best Submission", "comment_count": 8, "views": 0, "votes": 8, "reused": true }, { "id": 175317, "title": "4th to 456th Reaction", "comment_count": 4, "views": 0, "votes": 10, "reused": true }, { "id": 175330, "title": "105 place solution (0.9413 on LB). ", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175326, "title": "M A S S I V E", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 175321, "title": "The highest Private Score of public notebook. (0.9446)", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 175323, "title": "Thank you all very much)", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 175320, "title": "Such a tough Competition. Was it really CV?", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 175316, "title": "Need Help To Choose Best Model", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175227, "title": "No matter what happens, I will always trust my CV...", "comment_count": 5, "views": 0, "votes": 8, "reused": true }, { "id": 172357, "title": "Colab update to tensorflow 2.3 memory problem", "comment_count": 40, "views": 0, "votes": 30, "reused": true }, { "id": 175311, "title": "grab your popcorn", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 175301, "title": "Deadline for 3 competitions the same day, intense!", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 175309, "title": "Annoying consequence of new Kaggle interface - Can no longer do \"Find\" in discussions", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 175270, "title": "Incoming - earthquake on Private LB in 6 hr ", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 175297, "title": "Melanoma Classification GAN", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 175252, "title": "What just happened?", "comment_count": 13, "views": 0, "votes": 15, "reused": true }, { "id": 172830, "title": "Join SIIM AI Conference Virtually on 9/13-14", "comment_count": 6, "views": 0, "votes": 23, "reused": true }, { "id": 154296, "title": "Official External Data Thread", "comment_count": 108, "views": 0, "votes": 27, "reused": true }, { "id": 175274, "title": "MinMax or np.log ensemble", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 174622, "title": "With more complex models (b4,b5) both CV and LB go down", "comment_count": 18, "views": 0, "votes": 2, "reused": true }, { "id": 174806, "title": "Competition ends Aug 17 night, not Aug 18.", "comment_count": 5, "views": 0, "votes": 24, "reused": true }, { "id": 174657, "title": "Has anyone been dreaming about this competition? πŸ‘€", "comment_count": 16, "views": 0, "votes": 8, "reused": true }, { "id": 175095, "title": "It is all about ensembles in the last stage....", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 174729, "title": "Does anyone else wish more competitions were single model only?", "comment_count": 20, "views": 0, "votes": 53, "reused": true }, { "id": 175130, "title": "Good balance between CV/OOF and LB", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 175168, "title": "The way of learning Computer Vision algorithm", "comment_count": 2, "views": 0, "votes": -7, "reused": true }, { "id": 175177, "title": "Fast upload files", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 174956, "title": "How High-Score Kernels Doesn't Affect Us", "comment_count": 29, "views": 0, "votes": 1, "reused": true }, { "id": 175204, "title": "Best of luck! ", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 174116, "title": "Coding Song/playlist recommendation ", "comment_count": 11, "views": 0, "votes": 8, "reused": true }, { "id": 174897, "title": "The best single model CV/LB score?", "comment_count": 37, "views": 0, "votes": 5, "reused": true }, { "id": 175127, "title": "test data loading problem!", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 174515, "title": "Another 0.99+ team...", "comment_count": 51, "views": 0, "votes": 38, "reused": true }, { "id": 174923, "title": "PEP 8 Limiting our Data-Stories to 79 characters/line", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 155736, "title": "Better proportion of malignant images in test data", "comment_count": 1, "views": 0, "votes": 9, "reused": true }, { "id": 165963, "title": "Train on Pytorch slower than TensorFlow", "comment_count": 18, "views": 0, "votes": 3, "reused": true }, { "id": 174869, "title": "GAN Notebook to generate images ( Completed )", "comment_count": 9, "views": 0, "votes": 4, "reused": true }, { "id": 156027, "title": "Best Single Model", "comment_count": 177, "views": 0, "votes": 54, "reused": true }, { "id": 170846, "title": "Is GAN based melanoma generation allowed in this competition?", "comment_count": 24, "views": 0, "votes": 13, "reused": true }, { "id": 174320, "title": "Kaggle new Front-end design look worse than before", "comment_count": 15, "views": 0, "votes": 10, "reused": true }, { "id": 175036, "title": "Good luck to everyone.", "comment_count": 0, "views": 0, "votes": 7 }, { "id": 175007, "title": " Maybe a question outside of this competition. GPU quota.", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 174966, "title": "Does RANK BLEND method WORK?", "comment_count": 7, "views": 0, "votes": 5, "reused": true }, { "id": 174995, "title": "Autonencoder approach for Anomaly detection - notebook link ( TPU )", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 173020, "title": "AUC intuitively explained", "comment_count": 16, "views": 0, "votes": 73, "reused": true }, { "id": 172103, "title": "What is better? CNN with no meta INFO + Meta ensemble VS CNN with Meta", "comment_count": 3, "views": 0, "votes": 4, "reused": true }, { "id": 174489, "title": "Using TPU on Colab", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 174589, "title": "Estimate the Shake", "comment_count": 30, "views": 0, "votes": 56, "reused": true }, { "id": 173272, "title": "Pytorch user, try resnest instead of efficientnet", "comment_count": 35, "views": 0, "votes": 25, "reused": true }, { "id": 173808, "title": "So many things to try and one week left only...", "comment_count": 120, "views": 0, "votes": 56, "reused": true }, { "id": 174762, "title": "Google Colab TPU: OOM issues?", "comment_count": 11, "views": 0, "votes": 1, "reused": true }, { "id": 174602, "title": "Ensemble Techniques?", "comment_count": 14, "views": 0, "votes": 5, "reused": true }, { "id": 174743, "title": "Binary Cross Entropy and Focal Loss Ensemble", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 174757, "title": "TPU training, seems to hang, no progress", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 174820, "title": "Suggestions for final submission", "comment_count": 1, "views": 0, "votes": -16, "reused": true }, { "id": 163488, "title": "Thank you from a melanoma patient! ", "comment_count": 10, "views": 0, "votes": 78, "reused": true }, { "id": 171745, "title": "Interesting solution for 224 x 224 images (0.9287, no external data)", "comment_count": 11, "views": 0, "votes": 89, "reused": true }, { "id": 174503, "title": "MixUp implementation for Tensorflow datasets", "comment_count": 11, "views": 0, "votes": 6, "reused": true }, { "id": 174784, "title": "\"failed to connect to all addresses\" Error while using private Kaggle dataset on TPU...", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 173236, "title": "CV scores of your ensembles ", "comment_count": 65, "views": 0, "votes": 14, "reused": true }, { "id": 174269, "title": "ROC around 0.5 during training", "comment_count": 9, "views": 0, "votes": null, "reused": true }, { "id": 174528, "title": "Are you all using the same transforms in train, validation, OOF and test?", "comment_count": 16, "views": 0, "votes": 1, "reused": true }, { "id": 174699, "title": "OOF v/s LB", "comment_count": 1, "views": 0, "votes": -2, "reused": true }, { "id": 174735, "title": "What should be the steps_per_epoch for a model on TPU?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174712, "title": "Melanoma identification using \"contextual\" images", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 174299, "title": "ResourceExhaustedError when using TPU", "comment_count": 45, "views": 0, "votes": 15, "reused": true }, { "id": 173366, "title": "Adding Attention to EfficientNet", "comment_count": 5, "views": 0, "votes": 26, "reused": true }, { "id": 174045, "title": "Don't forget to use your gpu tensor cores", "comment_count": 9, "views": 0, "votes": 22, "reused": true }, { "id": 174321, "title": "2 input with custom Generator facing this issue ", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 174410, "title": " i was completely at a loss...", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 174522, "title": "More Resized Images", "comment_count": 2, "views": 0, "votes": 16, "reused": true }, { "id": 174317, "title": "How to make final submission using ensembles", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174349, "title": "Final submission", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174551, "title": "TF TPU with JPEGS?", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 173322, "title": "GPU Quota is increased to 39hrs per week", "comment_count": 11, "views": 0, "votes": 10, "reused": true }, { "id": 172904, "title": "Turbo charging data loading using c-types cache", "comment_count": 22, "views": 0, "votes": 7, "reused": true }, { "id": 174025, "title": "Tips and Tricks to make the most out of TPU ", "comment_count": 5, "views": 0, "votes": 7, "reused": true }, { "id": 154683, "title": "1st place solution in ISIC 2019 challenge (w/code)", "comment_count": 23, "views": 0, "votes": 174, "reused": true }, { "id": 174171, "title": "Where do you train?", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 174329, "title": "contextual information - sorry to bother again", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174312, "title": "Trying to load previously trained model weights but getting a TPU Compilation Error", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 154876, "title": "Color constancy as a pre-processing step", "comment_count": 8, "views": 0, "votes": 18, "reused": true }, { "id": 173951, "title": "Input to my notebook just vanished!!!", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 174012, "title": "Results of models other than efficientnet.", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 159476, "title": "Microscope augmentation", "comment_count": 29, "views": 0, "votes": 77, "reused": true }, { "id": 156934, "title": "YouTube tutorial on melanoma classification", "comment_count": 7, "views": 0, "votes": 15, "reused": true }, { "id": 173231, "title": "Optimal batch size on TPU for training", "comment_count": 14, "views": 0, "votes": 5, "reused": true }, { "id": 174435, "title": "Melanoma - Resource Exhausted Error ", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 174453, "title": "Numerous Output files ", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 174450, "title": "ISIC 2020 datasets with color normalized images (with color constancy)", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 174402, "title": "Need Good Public Kernels to learn/apply Ensembling", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 174058, "title": "Weights for different models - Ensemble", "comment_count": 15, "views": 0, "votes": 2, "reused": true }, { "id": 174117, "title": "Tips to increase TPU efficiency? ", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 174413, "title": "Custom LR Scheduler using Pytorch", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 173718, "title": "Training in parts vs together!", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 168028, "title": "Mystery Images - RAPIDS cuML TSNE", "comment_count": 22, "views": 0, "votes": 121, "reused": true }, { "id": 173117, "title": "pytorch and 384x384", "comment_count": 35, "views": 0, "votes": 2, "reused": true }, { "id": 174104, "title": "Beginner's Approach", "comment_count": 7, "views": 0, "votes": 2, "reused": true }, { "id": 174035, "title": "Call for Self-Nominations: TPU Stars", "comment_count": 3, "views": 0, "votes": 5, "reused": true }, { "id": 172799, "title": "Ideas from Google but tools for Pytorch ? ", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 174161, "title": "Why is tensorflow not support EfficientNet?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 174199, "title": "Normalization - CoarseDropout", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 174080, "title": "Ensuring better score than previously submitted submission file", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 173410, "title": "Training multiple big models on TPU with metadata", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 173724, "title": "Which external dataset to use as pytorch user ? ", "comment_count": 18, "views": 0, "votes": 2, "reused": true }, { "id": 173923, "title": "What I need to submit as an output of this competition?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 174027, "title": "Which custom head to use for EffficientNet?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154290, "title": "Looking for a Team Thread", "comment_count": 216, "views": 0, "votes": 21, "reused": true }, { "id": 169565, "title": "Congratulations to new notebooks grandmaster Laura Fink @allunia", "comment_count": 21, "views": 0, "votes": 42, "reused": true }, { "id": 171525, "title": "You May Choose 3 Final Submissions", "comment_count": 50, "views": 0, "votes": 46, "reused": true }, { "id": 172870, "title": "Changing the drop_connect_rate argument improves my EfficienNet model ", "comment_count": 8, "views": 0, "votes": 22, "reused": true }, { "id": 173772, "title": "how to use image data and tabular at once in keras with TPU.", "comment_count": 2, "views": 0, "votes": 0 }, { "id": 171930, "title": "10 Potential Private Test Leaks", "comment_count": 51, "views": 0, "votes": 86, "reused": true }, { "id": 161553, "title": "Final submission duration", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 172888, "title": "Using CUDA pin_memory and non_blocking to speed up workflows", "comment_count": 12, "views": 0, "votes": 2, "reused": true }, { "id": 173709, "title": "Kaggle notebook issues.", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 160867, "title": "submission without kernel?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 160430, "title": "Summary: Some Augmentations technique", "comment_count": 3, "views": 0, "votes": 27, "reused": true }, { "id": 173878, "title": "is it correct if there is some redundancy images in the data-set ??", "comment_count": 1, "views": 0, "votes": 1 }, { "id": 173852, "title": "My overall auc for one CV score lower than the average of each fold", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 173674, "title": "2 Model trained on Class 0 OR Class 1 only", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 173274, "title": "Higher score above 0.95", "comment_count": 11, "views": 0, "votes": 1, "reused": true }, { "id": 173859, "title": "Ensembling scores of different sized images.", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 169897, "title": "mixed precision with TPU tf.distrubute?", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 173834, "title": "Are we still able to make submissions?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 173684, "title": "How to upgrade TPU software version of Kaggle kernel from TF 2.2 to 2.3?", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 173438, "title": "Should we expect a shake-up?", "comment_count": 12, "views": 0, "votes": 12, "reused": true }, { "id": 173706, "title": "What is the value in case on Nan in TFRec datasets", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 172632, "title": "[FIXED] - Notebook Commit - JSON Error - Failed", "comment_count": 18, "views": 0, "votes": 13, "reused": true }, { "id": 173805, "title": "Image cropping strategy and image augmentation strategy", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 166697, "title": "Fast.ai (v. 1) starter with pretty good LB (0.926): EffNetB0 5-Fold with external data", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 172950, "title": "96.19LB score around 100 people achieved .... Really !!! What are you talking? ", "comment_count": 24, "views": 0, "votes": 5, "reused": true }, { "id": 173735, "title": "Any luck with BiT (Big transfer)?", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 173708, "title": "Various Evaluation Metrics (Beginners Can learn)", "comment_count": 1, "views": 0, "votes": 7, "reused": true }, { "id": 173632, "title": "Article on Melanoma Classification", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 173620, "title": "ROC - Predictions - Percentage Chance of Melanoma", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 173613, "title": "Ensembling and Networks outputs", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 173316, "title": "Need Help: AUC is always less that 0.5. What might be wrong with my model?", "comment_count": 14, "views": 0, "votes": null, "reused": true }, { "id": 166833, "title": "Pytorch Label Smoothing Implementation - Help Needed!", "comment_count": 12, "views": 0, "votes": 7, "reused": true }, { "id": 173628, "title": "can any one explain to me how we can apply over-sampling for this problem ???", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 172750, "title": "any one can tell me why im getting a problem when i try to print the score, precision, recall ", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 173633, "title": "to use f1_score in metrics", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 173365, "title": "People Started Ensembling?", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 171774, "title": "Patient-level label inconsistency", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 173404, "title": "Please help me with some suggestions, Pytorch users", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 173479, "title": "Best single model 0.953 but bad Ensembles, suggestions ? ", "comment_count": 8, "views": 0, "votes": 4, "reused": true }, { "id": 172816, "title": "Inconsistant CV and LB when adding Metadata", "comment_count": 6, "views": 0, "votes": 9, "reused": true }, { "id": 173191, "title": "Approaches summary ", "comment_count": 4, "views": 0, "votes": 25, "reused": true }, { "id": 173394, "title": "UnavailableError: Socket closed", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 173331, "title": "Kaggle TPU vs Colab TPU", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 173427, "title": "is freezing here a good idea for this problem ???", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 173224, "title": "0.9931 seems untouchable", "comment_count": 9, "views": 0, "votes": 1, "reused": true }, { "id": 173294, "title": "How can I install kaggle_datasets module?", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 173005, "title": "methods please and not submission ensembles", "comment_count": 4, "views": 0, "votes": 7, "reused": true }, { "id": 173242, "title": "With and without context submissions", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 173261, "title": "What tool are you using for annotation?", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 155251, "title": "Use Both Image Data and Tabular Data", "comment_count": 106, "views": 0, "votes": 141, "reused": true }, { "id": 173254, "title": "Using dual input models.", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 173229, "title": "Is anyone using BCE Label Smoothing with PyTorch?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 173195, "title": "multiple input model using keras api", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 173063, "title": "Train model with class weight ( [0.5478529 5.72434391] )", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 173086, "title": "ISIC 2018 - Winners Final 3 Submissions", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 172003, "title": "Higher Score.....!!!", "comment_count": 40, "views": 0, "votes": 14, "reused": true }, { "id": 172917, "title": "LB 96.19 at ONE SUBMISSION. What happened to LB?", "comment_count": 11, "views": 0, "votes": 4, "reused": true }, { "id": 164910, "title": "How To Use Last Years 2019 Comp Data (and 2018, 2017)", "comment_count": 58, "views": 0, "votes": 118, "reused": true }, { "id": 172975, "title": "XXL Average model experiment", "comment_count": 6, "views": 0, "votes": 4, "reused": true }, { "id": 172575, "title": "Prediction time is too long.", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 172863, "title": "can any one tell me how can i balance the data-set with tfrec files ???", "comment_count": 15, "views": 0, "votes": 4, "reused": true }, { "id": 172862, "title": "Tensorflow_Training and Prediction speed is very slow", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 172612, "title": "78 positive in public test?", "comment_count": 6, "views": 0, "votes": 16, "reused": true }, { "id": 172084, "title": "Question to kaggle TPU team", "comment_count": 8, "views": 0, "votes": 7, "reused": true }, { "id": 172695, "title": "KaggleDatasets().get_gcs_path~~~ Unauthenticated", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 172591, "title": "Why are we not freezing efficientnet's non-top layers?", "comment_count": 10, "views": 0, "votes": 3, "reused": true }, { "id": 172233, "title": "Publishing datasets and gcs_paths", "comment_count": 7, "views": 0, "votes": 5, "reused": true }, { "id": 172463, "title": "Do we need to normalize using ImageNet stats when we use pretrained EfficientNets?", "comment_count": 4, "views": 0, "votes": null }, { "id": 172684, "title": "Unexpected response from the service. while accessing the files", "comment_count": 1, "views": 0, "votes": 4, "reused": true }, { "id": 172019, "title": "Test time augmentations increases CV", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 171597, "title": "Accuracy 0.98", "comment_count": 13, "views": 0, "votes": 54, "reused": true }, { "id": 172663, "title": "Error while extracting GCS Path link", "comment_count": 5, "views": 0, "votes": 10, "reused": true }, { "id": 172511, "title": "CPU vs TPU usage", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 172302, "title": "Ensemble", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 172643, "title": "Problem with TPU ", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 170304, "title": "Is it necessary to input larger size images?", "comment_count": 11, "views": 0, "votes": null, "reused": true }, { "id": 166754, "title": "roc_auc_score and sigmoid", "comment_count": 26, "views": 0, "votes": 3, "reused": true }, { "id": 171801, "title": "Exploiting duplicate images", "comment_count": 29, "views": 0, "votes": 18, "reused": true }, { "id": 154281, "title": "Data loading is slow ?", "comment_count": 54, "views": 0, "votes": 9, "reused": true }, { "id": 172427, "title": "Separate prize for using Tabular Data", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 172252, "title": "filesystem access in tpu sessions seems slow since last night", "comment_count": 10, "views": 0, "votes": 7, "reused": true }, { "id": 169728, "title": "metadata don't want to cooperate", "comment_count": 42, "views": 0, "votes": 12, "reused": true }, { "id": 170945, "title": "TensorFlow backbones other than EfficientNet", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 172407, "title": "pseudo labelling with soft labels leads to bad results?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 172218, "title": "Pytorch equivalent of Keras scheduler everyone uses?", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 169434, "title": "About time", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 169488, "title": "CV vs Public Score", "comment_count": 8, "views": 0, "votes": 9, "reused": true }, { "id": 165352, "title": "4 Things that did not work!", "comment_count": 103, "views": 0, "votes": 62, "reused": true }, { "id": 172185, "title": "128 Tranforms and 128 Scores", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 172033, "title": "Large models (Batch size Vs Learning rate)", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 155306, "title": "using html to view images per patient", "comment_count": 13, "views": 0, "votes": 57, "reused": true }, { "id": 165598, "title": "Good validation accuracy, but low test score", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 171331, "title": "Simple average may be better than rank average", "comment_count": 11, "views": 0, "votes": 6, "reused": true }, { "id": 172183, "title": "Validation Batch Size for ROC / AUC", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 171982, "title": "Label Smoothing", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 171489, "title": "What augmentations / albumentations have you found most effective?", "comment_count": 6, "views": 0, "votes": 22, "reused": true }, { "id": 171954, "title": "Can we use submissions to run a regression on auc?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 171518, "title": "OpenCV2 > PIL-SIMD > PIL", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 171968, "title": "Dataset(external) simplified to 256,384,512,784 for ensemble", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 171514, "title": "Scikit-learn StratifiedGroupKFold", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 155579, "title": "TFRecords 768x768, 512x512, 384x384 With Meta Data", "comment_count": 77, "views": 0, "votes": 151, "reused": true }, { "id": 171785, "title": "One target for a patient?", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 170499, "title": "Are you opting for learning from image + metadata at together or seperatley ?", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 171778, "title": "Progressive Sprinkles Augmentation GPU/TPU", "comment_count": 2, "views": 0, "votes": 9, "reused": true }, { "id": 171768, "title": "Data Augmentation Idea: Generating new images when resizing them", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 170928, "title": "About Noisy Student (EfficientNet)", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 171339, "title": "training time is huge ", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 156476, "title": "Target leaks hunt started ...", "comment_count": 30, "views": 0, "votes": 18, "reused": true }, { "id": 171318, "title": "[tf.keras users] TTA wrapper of qubvel", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 171308, "title": "My TFRecords", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 167777, "title": "My Approach (95.2)", "comment_count": 27, "views": 0, "votes": 12, "reused": true }, { "id": 171207, "title": "Any way to avoid downloading 106 GB data? ", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 171003, "title": "Why is EfficientNet so popular in this competition?", "comment_count": 9, "views": 0, "votes": 4, "reused": true }, { "id": 163620, "title": "Installing PyTorch 1.6 in Kaggle environment", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 166006, "title": "What is the docker daemon error after 7 hours of GPU usage?", "comment_count": 16, "views": 0, "votes": null, "reused": true }, { "id": 170692, "title": "Utilizing GPU", "comment_count": 13, "views": 0, "votes": 5, "reused": true }, { "id": 171341, "title": "New image vs replacing the image while doing augmentation", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 171513, "title": "PyTorch: What are you all using for fast dataloading? LMDB, HFS5, Cache, etc?", "comment_count": 2, "views": 0, "votes": 5, "reused": true }, { "id": 170113, "title": "I am kaggle noobs, My CV and LB are so much inconsistent", "comment_count": 12, "views": 0, "votes": 1, "reused": true }, { "id": 169102, "title": "ImageDataGenerator with TPU", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 171103, "title": "Memory Allocation Error", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 171337, "title": "[Offtopic] On Comps Evaluation", "comment_count": 6, "views": 0, "votes": -3, "reused": true }, { "id": 170806, "title": "What is the efficient way to load data in colab?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 156614, "title": "Should we use class_weight to handle class imbalance ??", "comment_count": 3, "views": 0, "votes": 5, "reused": true }, { "id": 170569, "title": "Does color constancy help?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 171124, "title": "ensemble for AUC?", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 155705, "title": "power of external data", "comment_count": 8, "views": 0, "votes": 31, "reused": true }, { "id": 171027, "title": "Are other big model like PolyNet and SENet not suitable for this competition?", "comment_count": 9, "views": 0, "votes": 3, "reused": true }, { "id": 170911, "title": "Use openCV functions for images read by decode_jpeg in TF?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 155885, "title": "Feature engineering on metadata ", "comment_count": 20, "views": 0, "votes": 23, "reused": true }, { "id": 169980, "title": "Tip for those using frozen models", "comment_count": 1, "views": 0, "votes": 9, "reused": true }, { "id": 170812, "title": "Is the Kaggle data set crashed?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 170106, "title": "TPU utilizing 0%", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 170395, "title": "Hair Removal VS Addition ~", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 170611, "title": "Tensorflow and Image Processing!", "comment_count": 2, "views": 0, "votes": 5, "reused": true }, { "id": 165739, "title": "An easy and convenient way to look up GCS bucket addresses!", "comment_count": 2, "views": 0, "votes": 12, "reused": true }, { "id": 154347, "title": "Use Of TFrecords", "comment_count": 10, "views": 0, "votes": 10, "reused": true }, { "id": 170714, "title": "how to implement tabnet in keras or tensorflow ?", "comment_count": 1, "views": 0, "votes": null }, { "id": 170730, "title": "Starter with TResNet: A GPU-Dedicated Arch", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 169531, "title": "exhausted with errors", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 168020, "title": "how to work with this competition dataset on google colab?", "comment_count": 17, "views": 0, "votes": 2, "reused": true }, { "id": 170379, "title": "What should we use as a monitor? val_auc or val_loss?", "comment_count": 7, "views": 0, "votes": 6, "reused": true }, { "id": 170496, "title": "Image Shapes", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 170596, "title": "Why the probabilities are all under 0.5?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 170027, "title": "Anyone getting this????", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 170494, "title": "LGB/MLP/RIDGE STACKING Effnet OOF with META", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 170261, "title": "RIDGE/LGB/NN/ on meta data Optuna focal loss ", "comment_count": 7, "views": 0, "votes": 9, "reused": true }, { "id": 169985, "title": "Differential Learning Rates", "comment_count": 14, "views": 0, "votes": 11, "reused": true }, { "id": 155759, "title": "Body Hair Augmentation", "comment_count": 8, "views": 0, "votes": 11, "reused": true }, { "id": 161719, "title": "Shades of Gray prepossessed data (both JPEG's and tfrecords) ", "comment_count": 19, "views": 0, "votes": 18, "reused": true }, { "id": 170396, "title": "How does one use ensembles?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 169806, "title": "Image and Meta Data Extraction from tfrecords", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 170364, "title": "Notebook to use Images and Metadata in single EfNet B6 Model", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 169988, "title": "Start Small, Go Big", "comment_count": 5, "views": 0, "votes": 5, "reused": true }, { "id": 170179, "title": "external data and overfitting", "comment_count": 14, "views": 0, "votes": 2, "reused": true }, { "id": 170138, "title": "MobileNet On Melanoma", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 170063, "title": "Custom TFRecord on Colab TPU", "comment_count": 8, "views": 0, "votes": 4, "reused": true }, { "id": 169802, "title": "Good neural network playground", "comment_count": 9, "views": 0, "votes": 2, "reused": true }, { "id": 170075, "title": "Uncontrolled RAM growth - SIIM ISIC Melanoma", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 169262, "title": "Something wrong with strategy ? ", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 169963, "title": "Imputing patient_id", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 168914, "title": "Scale in the images: Is it a leak?", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 168641, "title": "How to run functions from other libraries in tensorflow data pipeline", "comment_count": 12, "views": 0, "votes": 3, "reused": true }, { "id": 165039, "title": "great ways of using Pre-trained models ", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 169340, "title": "Predictions Scatter Plot", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 169641, "title": "Efficient net training behaving weirdly", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 168253, "title": "How big is going to be the shake up?", "comment_count": 34, "views": 0, "votes": 19, "reused": true }, { "id": 169585, "title": "Why does the prediction or CV scores depend on Pytorch vs Tensorflow codes?", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 168849, "title": "Having trouble loading files", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 168582, "title": "Cannot access data anymore", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 169504, "title": "Batch form of affine augmentations in Tensor Flow", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 169389, "title": "Help please", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 155415, "title": "Few questions about the dicom files", "comment_count": 8, "views": 0, "votes": 16, "reused": true }, { "id": 169020, "title": "How to ensemble SRNext and Efficient?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 166571, "title": "GPU is not working", "comment_count": 9, "views": 0, "votes": 1, "reused": true }, { "id": 168954, "title": "Exploring The limits of Meta-Features using Custom Tabnet", "comment_count": 8, "views": 0, "votes": 10, "reused": true }, { "id": 169200, "title": "Which data augment technology is helpful for this competition?", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 167266, "title": "What is your best single model CV not LB score?", "comment_count": 13, "views": 0, "votes": 8, "reused": true }, { "id": 164020, "title": "pytorch and TPU", "comment_count": 26, "views": 0, "votes": 4, "reused": true }, { "id": 169136, "title": "How to get the CV score on ensemble models?", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 167945, "title": "Strategy for Meta-Data to increase LB score 0.001 ", "comment_count": 11, "views": 0, "votes": 8, "reused": true }, { "id": 167591, "title": "what have u learnt from this competition ?( any experience) ", "comment_count": 10, "views": 0, "votes": 9 }, { "id": 167217, "title": "I have a question about LRscheduler and Image augmentation", "comment_count": 12, "views": 0, "votes": 3, "reused": true }, { "id": 169140, "title": "Do Simple Average for Better Score", "comment_count": 9, "views": 0, "votes": 7, "reused": true }, { "id": 162035, "title": "focal loss for pytorch?", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 168632, "title": "Help in TFRecords", "comment_count": 11, "views": 0, "votes": null, "reused": true }, { "id": 168371, "title": "I want to use similar function that is pytorch 'Colorjitter' in Keras", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 168456, "title": "Ugly duckling detection - UMAP and pairwise distance", "comment_count": 6, "views": 0, "votes": 9, "reused": true }, { "id": 168647, "title": "Does multiple augmentations on dataset helps in increasing LB score ?", "comment_count": 4, "views": 0, "votes": null }, { "id": 166399, "title": "Ensemble is the key", "comment_count": 17, "views": 0, "votes": 11, "reused": true }, { "id": 168536, "title": "Struggling with preprocesing image in inference kernel! Too Slow!!!", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 168543, "title": "Is this normal or weird?", "comment_count": 22, "views": 0, "votes": null, "reused": true }, { "id": 168278, "title": "Kernel restart (RAM) right after training", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 168489, "title": "Tips for training big datasets", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 167573, "title": "Public High Accuracy Notebooks is not good", "comment_count": 17, "views": 0, "votes": 17, "reused": true }, { "id": 168290, "title": "Dataset for Research", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 167663, "title": "Training ETA is 5 hours when I added step_per_epoch with epoch=1", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 168466, "title": "How to get shape of image in tf.dataset?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 168458, "title": "How to interpret the AUC during training?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 168366, "title": "how long is your epoch on TPU?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 168422, "title": "Image quality may affect model performance", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 168334, "title": "Best Image Size??", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 166598, "title": "OpenCV GPU ??", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 168332, "title": "How to compute multi label class weight?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 168345, "title": "Huge gap between val_AUC and LB ?", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 168313, "title": "memory issues with shape 331,331,3 and batch size 8 with EFnet 6", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 167065, "title": "What is best method to experiment", "comment_count": 5, "views": 0, "votes": 3, "reused": true }, { "id": 168208, "title": "I made a dataset for PyTorch users that loads the jpg images easier!", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 168165, "title": "Thank YOU!", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 168186, "title": "Training time for 384x384 images on tpu(pytorch)", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 168073, "title": "Learn Deep learning by competing in SIIM-ISIC Melanoma Classification.", "comment_count": 5, "views": 0, "votes": 10, "reused": true }, { "id": 154658, "title": "Extract data from DICOM files", "comment_count": 2, "views": 0, "votes": 10, "reused": true }, { "id": 155216, "title": "GPU Problems", "comment_count": 10, "views": 0, "votes": 3, "reused": true }, { "id": 168095, "title": "Trained Models", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 167951, "title": "kernel is not utilizing gpu", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 167986, "title": "LB for 30% of data?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 167664, "title": "Keras vs PyTorch (and TFRecords)", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 167965, "title": "Data-Efficient Deep Learning Method for ImageClassification Using Data Augmentation, FocalCosine Loss, and Ensemble", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 167987, "title": "Starter with GhostNet Model, Thanks Alex Shonenkov", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 167795, "title": "[Info]: PyTorch, GhostNet-Pretrained Weights", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 165910, "title": "bad result when training with 8 TPU cores - OK on single core", "comment_count": 26, "views": 0, "votes": 4, "reused": true }, { "id": 166703, "title": "Using \"noisy-student\" is more powerful than \"imagenet\"", "comment_count": 24, "views": 0, "votes": 15, "reused": true }, { "id": 166733, "title": "Using diagnosis as secondary output", "comment_count": 11, "views": 0, "votes": 2, "reused": true }, { "id": 166634, "title": "Wellcome new quadruple GM", "comment_count": 23, "views": 0, "votes": 29, "reused": true }, { "id": 167227, "title": "Issue with GPU", "comment_count": 11, "views": 0, "votes": 1, "reused": true }, { "id": 167313, "title": "TPU without tfrecord", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 167518, "title": "πŸ”¬ Skin Lesions Detection", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 167215, "title": "[Updated] Distribution of test data 2.367%", "comment_count": 11, "views": 0, "votes": 24, "reused": true }, { "id": 159579, "title": "MXU usage / how to get the most out of TPUs?", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 167544, "title": "(tf.keras) How to release kernel RAM during inference?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 158414, "title": "Train & Test Intersections", "comment_count": 17, "views": 0, "votes": 46, "reused": true }, { "id": 167515, "title": "Anyone Using Metric Learning ? ", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 166975, "title": "Inference is too slow", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 166926, "title": "Melanoma - A Story in Three Parts", "comment_count": 2, "views": 0, "votes": 9, "reused": true }, { "id": 164309, "title": "Native Mixed Precision in PyTorch1.6+πŸ”₯", "comment_count": 8, "views": 0, "votes": 21, "reused": true }, { "id": 167359, "title": "What is the best score you can achieve using only tabular data?", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 167206, "title": "Does Over fitting mean model has enough parameters?", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 167262, "title": "Weight/snapshot ensembling? ", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 167210, "title": "Leaderboard Changed ?", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 167066, "title": "How to use FixEfficientNet??", "comment_count": 4, "views": 0, "votes": 7, "reused": true }, { "id": 167015, "title": "Cropping and Hue augmentations. Are they really useful?", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 166711, "title": "768x768 maybe the key", "comment_count": 17, "views": 0, "votes": 8, "reused": true }, { "id": 166267, "title": "[help] Can't understand the error given by model.fit()", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 166870, "title": "Model fitting with Map datasets ", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 166660, "title": "Combatting class imbalance question", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 166605, "title": "Resize the image from tfrecords", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 165223, "title": "Segmentation before classification", "comment_count": 15, "views": 0, "votes": 14, "reused": true }, { "id": 166614, "title": "Problem regarding Hair Augmentation using Tensorflow", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 154568, "title": "Resized Images", "comment_count": 34, "views": 0, "votes": 72, "reused": true }, { "id": 166155, "title": "Chris Deotte, Thank you! ", "comment_count": 12, "views": 0, "votes": 27, "reused": true }, { "id": 166497, "title": "ORB feature extraction and CNN avoiding", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 166167, "title": "No focal loss? Then how do you handle class imbalance?", "comment_count": 18, "views": 0, "votes": 3, "reused": true }, { "id": 166536, "title": "Some Doubts Regarding Melanoma Classification", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 156002, "title": "Implementation of Stratified Group K-Folds", "comment_count": 4, "views": 0, "votes": 16, "reused": true }, { "id": 166295, "title": "How to stabilize LB score for the same Experiment?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 165820, "title": "Public LB dramatically higher than local CV", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 166427, "title": "does down sampling works?", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 166424, "title": "Loading test image data set with PyTorch", "comment_count": 0, "views": 0, "votes": -1 }, { "id": 163641, "title": "Has anyone tried CutMix or MixUp augmentation successfully", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 166320, "title": "How does different sampling techniques makes difference?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 165213, "title": "binary_crossentropy vs categorical_crossentropy", "comment_count": 7, "views": 0, "votes": 2, "reused": true }, { "id": 160784, "title": "CutMix is tricky in this competition", "comment_count": 16, "views": 0, "votes": 22, "reused": true }, { "id": 164970, "title": "[solved?]PyTorch TPU is slower than PyTorch GPU", "comment_count": 8, "views": 0, "votes": 3, "reused": true }, { "id": 166126, "title": "Data augmentation EDA", "comment_count": 0, "views": 0, "votes": 8 }, { "id": 166121, "title": "FixEfficientNetB7 Noisy-student ", "comment_count": 1, "views": 0, "votes": 3, "reused": true }, { "id": 165669, "title": "TPU - how to save progress?", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 164594, "title": "\"Wonderful\" JPG", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 165623, "title": "Ensembling (for Vision) models", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 164560, "title": "πŸ”΄ 1st place solution in ISIC 2018 challenge [Youtube Video]", "comment_count": 11, "views": 0, "votes": 18, "reused": true }, { "id": 165402, "title": "Dense layer problem", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 164407, "title": "Looking for the optimal cross validation", "comment_count": 10, "views": 0, "votes": 4, "reused": true }, { "id": 164616, "title": "Pretraining on ISIC 2019 data hurts performance?", "comment_count": 11, "views": 0, "votes": 4, "reused": true }, { "id": 164989, "title": "Image Normalization", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 163944, "title": "accuracy shoots to 0.98 and validation to 0.96 in first epoch. is there something wrong?", "comment_count": 7, "views": 0, "votes": 0 }, { "id": 164956, "title": "free copy for a limited time Deep Learning with PyTorch", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 164995, "title": "Question for Organizer SIIM: Is using *diagnosis* column from train.csv considered as *With Context*?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 165212, "title": "Imbalanced Dataset Sampler! Better Sampler! Bert balance dataset", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 162396, "title": "Question for Organizer SIIM: Is train/validation splits by patient_id considered as **With Context**?", "comment_count": 5, "views": 0, "votes": 8, "reused": true }, { "id": 165194, "title": "Multi-Sample Dropout implement: Better Dropout! Better Accuracy!", "comment_count": 2, "views": 0, "votes": 13, "reused": true }, { "id": 164416, "title": "pytorch XLA......always allocate more memory than is available", "comment_count": 5, "views": 0, "votes": 6, "reused": true }, { "id": 160410, "title": "Best Loss function?", "comment_count": 16, "views": 0, "votes": 7, "reused": true }, { "id": 162281, "title": "Balanced and Segmented dataset.", "comment_count": 7, "views": 0, "votes": 11, "reused": true }, { "id": 164916, "title": "Colab KaggleDatasets() Issue", "comment_count": 12, "views": 0, "votes": 7, "reused": true }, { "id": 164752, "title": "AttributeError: module 'tensorflow.keras.applications' has no attribute 'EfficientNetB4'", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 164717, "title": "SIIM code requirements", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 161214, "title": "How to make pytorch TPU training faster??", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 163225, "title": "how to use ImageDataGenerator?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 155345, "title": "Using Stratified GroupKFold for CV", "comment_count": 5, "views": 0, "votes": 8, "reused": true }, { "id": 160312, "title": "Why are validation roc_auc_score and submission score so different?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 164481, "title": "TPU Training not working", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 164524, "title": "Help on AUC score Value Error", "comment_count": 10, "views": 0, "votes": null, "reused": true }, { "id": 163909, "title": "Advanced hair augmentation in TensorFlow", "comment_count": 15, "views": 0, "votes": 16, "reused": true }, { "id": 164664, "title": "Smaller Training Subset Download?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 164617, "title": "Is predicting Diagnosis better than predicting Target?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163501, "title": "Can we use TFrecords image format with ImageDataGenerator() ? ", "comment_count": 9, "views": 0, "votes": null }, { "id": 164612, "title": "size of the data (ISIC 2020 + 2019) and kaggle kernels", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 164311, "title": "i am an undergraduate student and just start learning this thing. Do you design you own architecture for competitions like this? help me out with some study material may be some book or tutorial?", "comment_count": 6, "views": 0, "votes": null }, { "id": 164514, "title": "How to cross 0.95", "comment_count": 7, "views": 0, "votes": 2, "reused": true }, { "id": 155201, "title": "dealing with fluctuating validation AUC in a single fold ", "comment_count": 23, "views": 0, "votes": 38, "reused": true }, { "id": 164354, "title": "Are you guys using any external data?", "comment_count": 4, "views": 0, "votes": null }, { "id": 164457, "title": "How to find image name for tfrecord image?", "comment_count": 1, "views": 0, "votes": null }, { "id": 164295, "title": "Using Class Weights During training", "comment_count": 3, "views": 0, "votes": 7, "reused": true }, { "id": 163805, "title": "Advanced Formatted Strings", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 163650, "title": "10015 lesion area segmentations", "comment_count": 4, "views": 0, "votes": 24, "reused": true }, { "id": 155433, "title": "Same patient ID having varied age values", "comment_count": 10, "views": 0, "votes": 3, "reused": true }, { "id": 163303, "title": "External packages not allowed?", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 164291, "title": "Which metric to use and workflow for model tuning", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 164268, "title": "Updated EDA and preprocessing", "comment_count": 0, "views": 0, "votes": -4 }, { "id": 154519, "title": "Preprocessed jpegs to 224x224 png", "comment_count": 4, "views": 0, "votes": 12, "reused": true }, { "id": 164248, "title": "Pytorch or keras ? What will you choose for this competition?", "comment_count": 1, "views": 0, "votes": null }, { "id": 164105, "title": "Kaggle Kernel vs Local: Data Loading Comparison ", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 163856, "title": "Progressive Augmentations with Pytorch?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 163606, "title": "Best architectures ensembles", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 160595, "title": "How to split TFRecords dataset based on class?", "comment_count": 2, "views": 0, "votes": 1 }, { "id": 160276, "title": "Help maximizing GPU. One epoch takes 5 hours with GPU.", "comment_count": 27, "views": 0, "votes": 3, "reused": true }, { "id": 161084, "title": "TPU or GPU?", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 163733, "title": "Got same prediction value for each image in test data?", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 163395, "title": "how to split images for training between two categories?", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 163611, "title": "Cuts?", "comment_count": 10, "views": 0, "votes": 1, "reused": true }, { "id": 163930, "title": "Does cropping hurt performance?", "comment_count": 4, "views": 0, "votes": 5, "reused": true }, { "id": 156263, "title": "Tips to make the most out of a kaggle GPU/TPU session", "comment_count": 19, "views": 0, "votes": 26, "reused": true }, { "id": 163754, "title": "My special list of what can be done", "comment_count": 8, "views": 0, "votes": 13, "reused": true }, { "id": 163932, "title": "Crash in data pre-processing step", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 163227, "title": "TFRecords 768x768, 384x384, 256x256 External Data", "comment_count": 7, "views": 0, "votes": 10, "reused": true }, { "id": 163893, "title": "Kaggle API support for TPU?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 163820, "title": "I cannnot use gpu", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 163667, "title": "Just a thought on competition", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 163697, "title": "Accuracy changes on moving from cpu to gpu", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 158395, "title": "TF/ TPU: from .tfrec to cross-validation. Step-by-step", "comment_count": 16, "views": 0, "votes": 48, "reused": true }, { "id": 161043, "title": "Resized JPG formats of the data", "comment_count": 5, "views": 0, "votes": 11, "reused": true }, { "id": 162476, "title": "ISIC 2018 dataset?", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 163602, "title": "Getting different scores with the same model and same input", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 163148, "title": "How to split a tf.data.TFRecordDataset to train and val datasets?", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 163422, "title": "How to deal with class imbalance?", "comment_count": 14, "views": 0, "votes": 4, "reused": true }, { "id": 163479, "title": "How to implement focal loss? and why focal loss performs better on this task then binary_crossentropy?", "comment_count": 2, "views": 0, "votes": null }, { "id": 163274, "title": "Valid Loss increasing but AUC score increasing too?", "comment_count": 11, "views": 0, "votes": 1, "reused": true }, { "id": 159015, "title": "Using colab vs kaggle notebooks", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 163188, "title": "New team!!!!!", "comment_count": 1, "views": 0, "votes": -1, "reused": true }, { "id": 162010, "title": "model overffitting because of the extremely in-banlanced training data", "comment_count": 11, "views": 0, "votes": null, "reused": true }, { "id": 163100, "title": "Using different filters for images", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 162857, "title": "Pre-trained CNN V/S Randomly initialize CNN models?", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 162933, "title": "Looking for teammate", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 160240, "title": "Best CV improvement over folds", "comment_count": 20, "views": 0, "votes": 3, "reused": true }, { "id": 161713, "title": "Need more runtime per run for TPUs!", "comment_count": 15, "views": 0, "votes": 5, "reused": true }, { "id": 160555, "title": "(CV VS LB) Which one should we trust?", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 162788, "title": "[Possible augmentation] Hair Removal from Images", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 162678, "title": "Can someone explain this augmentation matrix code?", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 159847, "title": "why is nobody talking about pseudo labeling here?", "comment_count": 12, "views": 0, "votes": 5, "reused": true }, { "id": 162469, "title": "Learning Resources", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 162393, "title": "Menzies Method and other Dermoscopy Algorithms", "comment_count": 4, "views": 0, "votes": 4, "reused": true }, { "id": 162533, "title": "the problems", "comment_count": 0, "views": 0, "votes": -3 }, { "id": 162446, "title": "Any suggestions to improve score ", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 161788, "title": "AUC monitoring in TF2", "comment_count": 8, "views": 0, "votes": null, "reused": true }, { "id": 161923, "title": "A Little Help", "comment_count": 21, "views": 0, "votes": null, "reused": true }, { "id": 162211, "title": "[PyTorch] Training on GPU takes too long", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 162398, "title": "Additional tabular data", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 162352, "title": "Congratulations to New Grandmaster Alex Shonenkov πŸ’›", "comment_count": 0, "views": 0, "votes": 6 }, { "id": 161681, "title": "Very low validation score", "comment_count": 7, "views": 0, "votes": 1, "reused": true }, { "id": 162015, "title": "The choice of optimizer", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 161528, "title": "Why training takes too much time with GPU ?", "comment_count": 9, "views": 0, "votes": null, "reused": true }, { "id": 162152, "title": "Resized Jpg Dataset : train + external dataset", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 161792, "title": "Best Research Papers for Competition", "comment_count": 2, "views": 0, "votes": 13, "reused": true }, { "id": 161052, "title": "Pytorch-XLA Installation Error", "comment_count": 5, "views": 0, "votes": 4, "reused": true }, { "id": 157701, "title": "[DBSCAN Clustering] Check Marking", "comment_count": 11, "views": 0, "votes": 36, "reused": true }, { "id": 161631, "title": "Can someone explain how TTA works in this competition?", "comment_count": 11, "views": 0, "votes": 2, "reused": true }, { "id": 158860, "title": "Focal loss testing results - Did you have a similar experience?", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 160762, "title": "Having a reliable CV strategy", "comment_count": 7, "views": 0, "votes": 8, "reused": true }, { "id": 161674, "title": "Confusion about the feature formats of tfrecord files.", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 158380, "title": "Data pre-processing for Melanoma Classification", "comment_count": 4, "views": 0, "votes": 7, "reused": true }, { "id": 161712, "title": "Missing data in original dataset", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 155348, "title": "understanding \"Ugly Duckling Concept\"", "comment_count": 9, "views": 0, "votes": 36, "reused": true }, { "id": 161627, "title": "Stratified Kfold", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 161597, "title": "Trouble: Focal Loss with FP16 training ", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 156685, "title": "Output File not generated", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 161560, "title": "Keras stop working at 2nd epoch.", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 161401, "title": "The right way of dealing with external data?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 154659, "title": "Tools for exploring DICOM files", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 161393, "title": "Accessing public data", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 160697, "title": "External data", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 161207, "title": "TPU get_gcs_path for local files", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 156064, "title": "Beware of non-calibrated predictions", "comment_count": 10, "views": 0, "votes": 56, "reused": true }, { "id": 160924, "title": "The Kernel has been Stopped after 3 hours of TPU continuos use", "comment_count": 4, "views": 0, "votes": 1, "reused": true }, { "id": 160136, "title": "DICOM or jpeg?", "comment_count": 6, "views": 0, "votes": 5, "reused": true }, { "id": 160939, "title": "Getting this error. Can anyone help me resolve?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 160791, "title": "Efficiently using cost-efficient cloud GPU's/TPU's for Kaggle competitions", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 160907, "title": "Don't forget to check the distribution of your submission :)", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 160782, "title": "Choice of Models", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 158747, "title": "Request to Kaggle - Organize the external data thread", "comment_count": 17, "views": 0, "votes": 17, "reused": true }, { "id": 160626, "title": "No Dataset API to download?", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 160388, "title": "What does your Kaggle Pipeline look like?", "comment_count": 5, "views": 0, "votes": 5, "reused": true }, { "id": 154514, "title": "Question to Kaggle", "comment_count": 11, "views": 0, "votes": 22, "reused": true }, { "id": 156533, "title": "Augmentations and Data Storage", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 160702, "title": "Use cross entropy loss (NOT BCE) for focal loss calculation", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 160692, "title": "512x512 jpeg images of competition", "comment_count": 0, "views": 0, "votes": 12 }, { "id": 159456, "title": "Download any specific folder easily with this method", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 157273, "title": "ResourceExhaustedError", "comment_count": 4, "views": 0, "votes": 2, "reused": true }, { "id": 160495, "title": "Different Data Augmentation Techniques", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 159580, "title": "Integration of image and tabular data (metadata) for fastai users ", "comment_count": 3, "views": 0, "votes": 3, "reused": true }, { "id": 156038, "title": "Melanoma Starter", "comment_count": 5, "views": 0, "votes": 21, "reused": true }, { "id": 158975, "title": "how to download kaggle dataset through terminal ? ", "comment_count": 8, "views": 0, "votes": 2, "reused": true }, { "id": 160238, "title": "External Model Weights", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 160171, "title": "Image Augmentation", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 156403, "title": "Q. How can I perform Image Augmentation only for the Minority class?", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 160149, "title": "How to create a valid dataset and what metric to use for EarlyStopping?", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 158504, "title": "GPU is not working", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 157361, "title": "Unable to extract properly in Colab", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 159777, "title": "Magical val_accuracy level: what is it?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 159143, "title": "Different malignant images in ISIC 2019", "comment_count": 8, "views": 0, "votes": 7, "reused": true }, { "id": 159101, "title": "Yet another dataset with external data", "comment_count": 3, "views": 0, "votes": 15, "reused": true }, { "id": 157576, "title": "Notebook Disconnected during Training", "comment_count": 6, "views": 0, "votes": 1, "reused": true }, { "id": 158861, "title": "What image augmentation methods worked best?", "comment_count": 3, "views": 0, "votes": 2, "reused": true }, { "id": 159140, "title": "Higher number of epochs = better score?", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 159670, "title": "New and updated EDA with necessary pre-processing", "comment_count": 0, "views": 0, "votes": -2 }, { "id": 159640, "title": "kfold did not improve acc", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 159613, "title": "SIIM-ISIC 256x256 : Features from DenseNet169, DenseNet201, ...", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 154464, "title": "Any way to download a specific folder in google colab?", "comment_count": 8, "views": 0, "votes": 5, "reused": true }, { "id": 159427, "title": "Copy of NN doesn't work as original did", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 154364, "title": "Kaggle API jpeg only downloads", "comment_count": 12, "views": 0, "votes": 22, "reused": true }, { "id": 158798, "title": "External data DOES NOT need to be public to get ranking points and medals [Confirmed]", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 159367, "title": "UnavailableError: Socket closed", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 159257, "title": "EfficientNet Size x Performance", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 158941, "title": "GPU not working", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 159163, "title": "EDA with necessary image pre-processing", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 159102, "title": "How do I plot confusion matrix?", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 158895, "title": "Tabular Modeling With TabNet", "comment_count": 3, "views": 0, "votes": 12, "reused": true }, { "id": 155668, "title": "Reaching 0.9 with ResNet18 and 256x256 images", "comment_count": 46, "views": 0, "votes": 39, "reused": true }, { "id": 159064, "title": "Weird Predictions", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 156532, "title": "Data Augmentation", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 158682, "title": "Informed Consent External Data", "comment_count": 3, "views": 0, "votes": 7, "reused": true }, { "id": 158967, "title": "Some files raise 404 not found when trying to download them with kaggle api in colab", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 158304, "title": "GPU is not getting used, Any suggestion,Please need help πŸ™πŸ™πŸ™", "comment_count": 10, "views": 0, "votes": 1, "reused": true }, { "id": 158236, "title": "Strange occurences", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 158848, "title": "TPU MXU unit", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 158620, "title": "Colab + Kaggle API - not listing all files", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 158668, "title": "No files in '/kaggle/input/'", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 155317, "title": "Unbalanced classes and CNN", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 158149, "title": "KFold Implementation help", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 158520, "title": "Kaggle NoteBook RAM is exceeding", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 157060, "title": "AUC Metric", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 158349, "title": "'Request Merge' button is NOT active", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 156284, "title": "Dixon's Q-test to identify \"Ugly duckling\" outliers", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 158484, "title": "Papers for Recommended Augmentations for Problem", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 157109, "title": "[Torch XLA] Melanoma Crazy Fast", "comment_count": 5, "views": 0, "votes": 19, "reused": true }, { "id": 157839, "title": "Reading TFRecords from local or Kaggle datasets on TPUs", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 158168, "title": "Loading data using Pytorch Dataset", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 157960, "title": "Can't generate same results from previous public notebooks!!!!", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 157973, "title": "Combining Tabular + Vision in fastai2", "comment_count": 0, "views": 0, "votes": 5 }, { "id": 157499, "title": "How to set up a good CV strategy ?", "comment_count": 3, "views": 0, "votes": 9, "reused": true }, { "id": 155874, "title": "Some great resources to start with", "comment_count": 1, "views": 0, "votes": 8, "reused": true }, { "id": 154669, "title": "LB speculation", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 157819, "title": "Starter Tensorflow Kernel", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 156616, "title": "Column \"age_approx\" meaning", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 156713, "title": "Size of each image - 2 groups", "comment_count": 3, "views": 0, "votes": 12, "reused": true }, { "id": 157672, "title": "Beginner question: minimum hardware specification", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 157612, "title": "TPU: compile within or outside scope", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 157632, "title": "How to mix metadata with image-classification?", "comment_count": 2, "views": 0, "votes": 3, "reused": true }, { "id": 156998, "title": "Don't underestimate the Tabular data!!! [LB: .818]", "comment_count": 10, "views": 0, "votes": 16, "reused": true }, { "id": 157135, "title": "TF dynamic dimension issue", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 157589, "title": "TPU Usage at 0%", "comment_count": 1, "views": 0, "votes": 1, "reused": true }, { "id": 157383, "title": "[Advice Needed] Hyperparameter/Architecture tuning", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 157337, "title": "Sometimes can't access the data", "comment_count": 6, "views": 0, "votes": 3, "reused": true }, { "id": 155963, "title": "TPU HTTP Connection Error", "comment_count": 17, "views": 0, "votes": 9, "reused": true }, { "id": 157289, "title": "Anyone facing connection time out on get_gcs_path?", "comment_count": 5, "views": 0, "votes": 1, "reused": true }, { "id": 157279, "title": "KaggleDatasets HTTP Error(TPU)", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 157255, "title": "Weighting false positives vs false negatives", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 157238, "title": "Adversarial Validation 2 - Metadata and Image Size", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 156890, "title": "Melanoma Classification with Attention. ", "comment_count": 2, "views": 0, "votes": 8, "reused": true }, { "id": 156995, "title": "Your TPU notebook stops after 15 minutes", "comment_count": 7, "views": 0, "votes": null, "reused": true }, { "id": 154733, "title": "CV vs LB", "comment_count": 21, "views": 0, "votes": 12, "reused": true }, { "id": 156946, "title": "TFRecords Data Augmentation", "comment_count": 8, "views": 0, "votes": 1, "reused": true }, { "id": 157123, "title": "cvpr2020 workshop \"Skin Image Analysis\": the new papers are out", "comment_count": 0, "views": 0, "votes": 11 }, { "id": 157050, "title": "Focal loss nan values", "comment_count": 3, "views": 0, "votes": -2, "reused": true }, { "id": 157059, "title": "Torso cancer is more prevalent in the dataset, not most likely to be malign ", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 156359, "title": "Special Prize Question : Context and Non-Context", "comment_count": 4, "views": 0, "votes": 6, "reused": true }, { "id": 156794, "title": "Saving preprocessed data - Kernel Output limit size", "comment_count": 5, "views": 0, "votes": null, "reused": true }, { "id": 156482, "title": "Beginner Advice", "comment_count": 6, "views": 0, "votes": null, "reused": true }, { "id": 156691, "title": "Resources Melanoma Detection that help you for approach", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 155181, "title": "Where do the perfects come from? How much can I trust them?", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 156321, "title": "Kaggle slow GPU Training ", "comment_count": 15, "views": 0, "votes": 2, "reused": true }, { "id": 156339, "title": "Is 128x128 better than 32x32", "comment_count": 7, "views": 0, "votes": 3, "reused": true }, { "id": 156516, "title": "Relevant paper and video", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 155924, "title": "Beginner in CNN", "comment_count": 12, "views": 0, "votes": 7, "reused": true }, { "id": 156251, "title": "The evaluation metric (ROC curve)", "comment_count": 5, "views": 0, "votes": 2, "reused": true }, { "id": 156407, "title": "Problem with fastai library", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 156405, "title": "Advice Needed !!", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 156386, "title": " [TF.Keras] Melanoma Starter (GPU)", "comment_count": 2, "views": 0, "votes": 6, "reused": true }, { "id": 155296, "title": "what is \"diagnosis=unknown\" in the csv train file?", "comment_count": 7, "views": 0, "votes": 4, "reused": true }, { "id": 156303, "title": "GPU makes no difference", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 156334, "title": "Could we ask to add more decimals?", "comment_count": 0, "views": 0, "votes": 10 }, { "id": 155624, "title": "Download individual folders via python", "comment_count": 3, "views": 0, "votes": 10, "reused": true }, { "id": 156237, "title": "use β€˜ABCD’ rules", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 156195, "title": "another unbalanced dataset", "comment_count": 0, "views": 0, "votes": -8 }, { "id": 156169, "title": "[Bug Fixed] StratifyGroupKfold", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 156153, "title": "Extract image features (w/ ImageNet weights)", "comment_count": 2, "views": 0, "votes": 4, "reused": true }, { "id": 155928, "title": "Augmentation and Size Techniques", "comment_count": 1, "views": 0, "votes": 2, "reused": true }, { "id": 156030, "title": "Different Augmentations", "comment_count": 0, "views": 0, "votes": 3 }, { "id": 155986, "title": "folding vs not folding", "comment_count": 0, "views": 0, "votes": 1 }, { "id": 155459, "title": "Resized JPG Images: 300x300 & 640x640", "comment_count": 3, "views": 0, "votes": 11, "reused": true }, { "id": 155932, "title": "Getting nan as model output", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 155925, "title": "Development Setup for CNN training", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 155773, "title": "Download data on external server?", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 155697, "title": "Confused about TFRecords", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 155738, "title": "ABCDE is letters of the alphabet, which are a guide to help you recognize the warning signs of melanoma.", "comment_count": 1, "views": 0, "votes": 11, "reused": true }, { "id": 155754, "title": "[Help Needed] !pip install not working", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 155749, "title": "Weird error while training the model on TPU", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 155739, "title": "Useful Research Papers ", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 155693, "title": "Generating new data?", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 154791, "title": "How should I deal with this highly imbalanced data? Any SuggestionsπŸ™", "comment_count": 14, "views": 0, "votes": 13, "reused": true }, { "id": 155664, "title": "What type of error is this????", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 155672, "title": "Abhishek Thakur explaining SIIM-ISIC Melanoma Classification", "comment_count": 2, "views": 0, "votes": 9, "reused": true }, { "id": 155069, "title": "For the ones who only need to download specific folder", "comment_count": 9, "views": 0, "votes": 9, "reused": true }, { "id": 155617, "title": "Got letter from Kaggle team: what the...", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 155367, "title": "tf.dataset tpu pipeline augmentation other than tf.image", "comment_count": 6, "views": 0, "votes": 2, "reused": true }, { "id": 155360, "title": "Some Research paper Related to Skin Cancer...", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 154501, "title": "Metric will change?", "comment_count": 3, "views": 0, "votes": 6, "reused": true }, { "id": 154890, "title": "How to split a validation dataset from TFrecords?", "comment_count": 3, "views": 0, "votes": 1 }, { "id": 154475, "title": "Organizers, thank you <3", "comment_count": 10, "views": 0, "votes": 4, "reused": true }, { "id": 155331, "title": "Is there any role of patients details in detection?", "comment_count": 0, "views": 0, "votes": 0 }, { "id": 155237, "title": "Careful about data leakage?", "comment_count": 4, "views": 0, "votes": 3, "reused": true }, { "id": 155190, "title": "Is this due to the heavily imbalanced data?", "comment_count": 2, "views": 0, "votes": 2, "reused": true }, { "id": 155113, "title": "Submission question", "comment_count": 3, "views": 0, "votes": null, "reused": true }, { "id": 155227, "title": "Kaggle Notebooks Timeout", "comment_count": 2, "views": 0, "votes": null, "reused": true }, { "id": 154844, "title": "Don't flip your labels", "comment_count": 11, "views": 0, "votes": 1, "reused": true }, { "id": 155011, "title": "A Look at the Data with t-SNE and UMAP dimensionality reduction algorithms", "comment_count": 3, "views": 0, "votes": 4, "reused": true }, { "id": 154906, "title": "66% chance of correct classifying based only on patient info", "comment_count": 2, "views": 0, "votes": 13, "reused": true }, { "id": 154918, "title": "Looking for Teammate", "comment_count": 1, "views": 0, "votes": -1, "reused": true }, { "id": 154848, "title": "Too many requests error", "comment_count": 4, "views": 0, "votes": null, "reused": true }, { "id": 154285, "title": "Previous works for inspiration", "comment_count": 7, "views": 0, "votes": 42, "reused": true }, { "id": 154817, "title": "Input features in tfrec files", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154755, "title": "Pytorch Lightning Starter notebook [0.879]", "comment_count": 1, "views": 0, "votes": 7, "reused": true }, { "id": 154440, "title": "It's AUC but ...", "comment_count": 9, "views": 0, "votes": 9, "reused": true }, { "id": 154738, "title": "Data provenance", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154785, "title": "Adversarial Validation on Pixel Data", "comment_count": 1, "views": 0, "votes": 6, "reused": true }, { "id": 154278, "title": "Teaming up and looking to join a Team", "comment_count": 7, "views": 0, "votes": -1, "reused": true }, { "id": 154624, "title": "how many public test samples are positive?", "comment_count": 3, "views": 0, "votes": 13, "reused": true }, { "id": 154340, "title": "CLI download links?", "comment_count": 3, "views": 0, "votes": 1, "reused": true }, { "id": 154536, "title": "Help with metric", "comment_count": 2, "views": 0, "votes": 1, "reused": true }, { "id": 154457, "title": "Submission limits for a team of 5?", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154380, "title": "My best work (EDA for this competition)", "comment_count": 0, "views": 0, "votes": 4 }, { "id": 154375, "title": "Some Useful links related to Dicom Image ", "comment_count": 0, "views": 0, "votes": 2 }, { "id": 154339, "title": "Training Data Creation", "comment_count": 1, "views": 0, "votes": null, "reused": true }, { "id": 154322, "title": "EfficientNet Weights for Keras", "comment_count": 1, "views": 0, "votes": 3, "reused": true } ], "errors": [ { "id": 543294, "error": "topic 543294 comments still failing after 3 tries (HTTP 429 body_len 82); not treating it as empty" }, { "id": 155902, "error": "topic 155902 comments still failing after 3 tries (HTTP 429 body_len 82); not treating it as empty" } ] }