{ "id": 582269, "title": "Starter materials and onboarding resources ", "url": "/competitions/cmi-detect-behavior-with-sensor-data/discussion/582269", "author_name": "", "post_date": "2025-05-30T06:56:06.820421900Z", "votes": 5, "comment_count": 2, "views": 0, "content": "

Hello all,

\n

All the best for the time series tabular challenge! Hope the below materials are of use to start off well here. We have a number of time series artefacts for reference here-

\n

Child Mind Institute - Detect Sleep States

\n

Most voted kernels

\n\n

Top ranked solutions

\n\n

Jane Street Market Prediction

\n

Most voted kernels

\n\n

Top ranked solutions

\n\n

Jane Street Real-Time Market Data Forecasting

\n

Most voted kernels

\n\n

Similar Kaggle competition references

\n

ASHRAE - Great Energy Predictor III

\n

Kernels- top 5 voted

\n
    \n
  1. https://www.kaggle.com/code/caesarlupum/ashrae-start-here-a-gentle-introduction
    2. \n
  2. https://www.kaggle.com/code/nroman/eda-for-ashrae
    3. \n
  3. https://www.kaggle.com/code/rohanrao/ashrae-half-and-half
    4. \n
  4. https://www.kaggle.com/code/corochann/optuna-tutorial-for-hyperparameter-optimization
    5. \n
  5. https://www.kaggle.com/code/corochann/ashrae-training-lgbm-by-meter-type
    6. \n
\n

Kernels- top 3 scores

\n
    \n
  1. https://www.kaggle.com/code/patrick0302/postprocessed-models-bland-by-leak
    2. \n
  2. https://www.kaggle.com/code/vladimirsydor/add-leak
    3. \n
  3. https://www.kaggle.com/code/gpamoukoff/ashrae-subm-stack-fin-3
    4. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124709 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123481 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124984 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124788 --rank4
    5. \n
  5. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/127086 --rank5
    6. \n
  6. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123525 -- rank9
    7. \n
\n

Other useful posts and discussions

\n
    \n
  1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/112872
    2. \n
  2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/114345
    3. \n
  3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/113678
    4. \n
  4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/115698
    5. \n
\n

Optiver- Trading at the Close

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models
    2. \n
  2. https://www.kaggle.com/code/yuanzhezhou/baseline-lgb-xgb-and-catboost
    3. \n
  3. https://www.kaggle.com/code/a27182818/explain-the-data-lightgbm-baseline
    4. \n
  4. https://www.kaggle.com/code/lblhandsome/optiver-robust-best-single-model
    5. \n
  5. https://www.kaggle.com/code/verracodeguacas/fold-cv
    6. \n
  6. https://www.kaggle.com/code/peizhengwang/best-public-score
    7. \n
  7. https://www.kaggle.com/code/siddhvr/optiver-trading-at-the-close-sub
    8. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/487446
    2. \n
  2. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486868
    3. \n
  3. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/462653
    4. \n
  4. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486086
    5. \n
\n

Enefit - Predict Energy Behavior of Prosumers

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/rafiko1/enefit-xgboost-starter
    2. \n
  2. https://www.kaggle.com/code/vitalykudelya/explain-dataset-and-baseline
    3. \n
  3. https://www.kaggle.com/code/vincentschuler/enefit-baseline-cross-validation
    4. \n
  4. https://www.kaggle.com/code/greysky/enefit-generic-notebook
    5. \n
  5. https://www.kaggle.com/code/vitalykudelya/enefit-target-diff
    6. \n
  6. https://www.kaggle.com/code/ahmedabdulwahab/pandas-data-description-and-starters-guide
    7. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472793
    2. \n
  2. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499938
    3. \n
  3. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499397
    4. \n
  4. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499649
    5. \n
  5. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537
    6. \n
  6. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537
    7. \n
\n

Playground Time Series Forecasting challenges

\n

Season3-Episode 20

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ambrosm/pss3e20-eda-which-makes-sense
    2. \n
  2. https://www.kaggle.com/code/kacperrabczewski/rwanda-co2-step-by-step-guide
    3. \n
  3. https://www.kaggle.com/code/yaaangzhou/pg-s3-e20-eda-modeling
    4. \n
  4. https://www.kaggle.com/code/dmitryuarov/ps3e20-rwanda-emission-advanced-fe-20-88
    5. \n
  5. https://www.kaggle.com/code/iqbalsyahakbar/ps3e20-time-series-for-beginners
    6. \n
\n

Season3-Episode 19

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/tumpanjawat/s3e19-course-eda-fe-lightgbm
    2. \n
  2. https://www.kaggle.com/code/iqbalsyahakbar/ps3e19-time-series-for-beginners
    3. \n
  3. https://www.kaggle.com/code/ivyzang/1st-place-solution-less-is-more
    4. \n
  4. https://www.kaggle.com/code/tetsutani/ps3e19-eda-ensemble-ml-pipeline-rnn-by-skorch
    5. \n
  5. https://www.kaggle.com/code/kacperrabczewski/last-minute-forecasting
    6. \n
\n

TPS- September2022

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/azminetoushikwasi/time-series-analysis-forecasting
    2. \n
  2. https://www.kaggle.com/code/cabaxiom/tps-sep-22-eda-and-linear-regression-baseline
    3. \n
  3. https://www.kaggle.com/code/khashayarrahimi94/why-you-should-not-use-correlation
    4. \n
  4. https://www.kaggle.com/code/vencerlanz09/tps-eda-9-models-explanation
    5. \n
  5. https://www.kaggle.com/code/samuelcortinhas/tps-sept-22-timeseries-analysis
    6. \n
\n

TPS- January2022

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ambrosm/tpsjan22-03-linear-model
    2. \n
  2. https://www.kaggle.com/code/ambrosm/tpsjan22-01-eda-which-makes-sense
    3. \n
  3. https://www.kaggle.com/code/usharengaraju/tensorflow-tf-data-keraspreprocessinglayers-w-b
    4. \n
  4. https://www.kaggle.com/code/teckmengwong/tps2201-hybrid-time-series
    5. \n
  5. https://www.kaggle.com/code/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex
    6. \n
\n

GoDaddy - Microbusiness Density Forecasting

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/titericz/better-xgb-baseline
    2. \n
  2. https://www.kaggle.com/code/cdeotte/linear-regression-baseline-lb-1-092
    3. \n
  3. https://www.kaggle.com/code/tanmay111999/gdmbf-ar-ma-arma-arima-sarima-auto-arima
    4. \n
  4. https://www.kaggle.com/code/cdeotte/seasonal-model-with-validation-lb-1-091
    5. \n
  5. https://www.kaggle.com/code/kimtaehun/complete-baseline-code-with-various-ml-model
    6. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395131 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395264 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/418287 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/394821 -- rank4
    5. \n
\n

Miscellaneous kernel references on time series-

\n
    \n
  1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models
    2. \n
  2. https://www.kaggle.com/code/kanncaa1/time-series-prediction-tutorial-with-eda
    3. \n
  3. https://www.kaggle.com/code/freespirit08/time-series-for-beginners-with-arima
    4. \n
  4. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-prophet
    5. \n
  5. https://www.kaggle.com/code/iamleonie/intro-to-time-series-forecasting
    6. \n
  6. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-machine-learning-yt
    7. \n
  7. https://www.kaggle.com/code/rohanrao/a-modern-time-series-tutorial
    8. \n
  8. https://www.kaggle.com/code/cdeotte/time-series-eda
    9. \n
  9. https://www.kaggle.com/code/janiobachmann/s-p-500-time-series-forecasting-with-prophet
    10. \n
  10. https://www.kaggle.com/code/robikscube/pt2-time-series-forecasting-with-xgboost
    11. \n
\n

Wishing you the best for the assignment and happy learning!

", "messages": [ { "id": "3213547", "postDate": "05/30/2025 06:56:06", "content": "

Hello all,

\n

All the best for the time series tabular challenge! Hope the below materials are of use to start off well here. We have a number of time series artefacts for reference here-

\n

Child Mind Institute - Detect Sleep States

\n

Most voted kernels

\n\n

Top ranked solutions

\n\n

Jane Street Market Prediction

\n

Most voted kernels

\n\n

Top ranked solutions

\n\n

Jane Street Real-Time Market Data Forecasting

\n

Most voted kernels

\n\n

Similar Kaggle competition references

\n

ASHRAE - Great Energy Predictor III

\n

Kernels- top 5 voted

\n
    \n
  1. https://www.kaggle.com/code/caesarlupum/ashrae-start-here-a-gentle-introduction
    2. \n
  2. https://www.kaggle.com/code/nroman/eda-for-ashrae
    3. \n
  3. https://www.kaggle.com/code/rohanrao/ashrae-half-and-half
    4. \n
  4. https://www.kaggle.com/code/corochann/optuna-tutorial-for-hyperparameter-optimization
    5. \n
  5. https://www.kaggle.com/code/corochann/ashrae-training-lgbm-by-meter-type
    6. \n
\n

Kernels- top 3 scores

\n
    \n
  1. https://www.kaggle.com/code/patrick0302/postprocessed-models-bland-by-leak
    2. \n
  2. https://www.kaggle.com/code/vladimirsydor/add-leak
    3. \n
  3. https://www.kaggle.com/code/gpamoukoff/ashrae-subm-stack-fin-3
    4. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124709 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123481 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124984 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124788 --rank4
    5. \n
  5. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/127086 --rank5
    6. \n
  6. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123525 -- rank9
    7. \n
\n

Other useful posts and discussions

\n
    \n
  1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/112872
    2. \n
  2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/114345
    3. \n
  3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/113678
    4. \n
  4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/115698
    5. \n
\n

Optiver- Trading at the Close

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models
    2. \n
  2. https://www.kaggle.com/code/yuanzhezhou/baseline-lgb-xgb-and-catboost
    3. \n
  3. https://www.kaggle.com/code/a27182818/explain-the-data-lightgbm-baseline
    4. \n
  4. https://www.kaggle.com/code/lblhandsome/optiver-robust-best-single-model
    5. \n
  5. https://www.kaggle.com/code/verracodeguacas/fold-cv
    6. \n
  6. https://www.kaggle.com/code/peizhengwang/best-public-score
    7. \n
  7. https://www.kaggle.com/code/siddhvr/optiver-trading-at-the-close-sub
    8. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/487446
    2. \n
  2. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486868
    3. \n
  3. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/462653
    4. \n
  4. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486086
    5. \n
\n

Enefit - Predict Energy Behavior of Prosumers

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/rafiko1/enefit-xgboost-starter
    2. \n
  2. https://www.kaggle.com/code/vitalykudelya/explain-dataset-and-baseline
    3. \n
  3. https://www.kaggle.com/code/vincentschuler/enefit-baseline-cross-validation
    4. \n
  4. https://www.kaggle.com/code/greysky/enefit-generic-notebook
    5. \n
  5. https://www.kaggle.com/code/vitalykudelya/enefit-target-diff
    6. \n
  6. https://www.kaggle.com/code/ahmedabdulwahab/pandas-data-description-and-starters-guide
    7. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472793
    2. \n
  2. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499938
    3. \n
  3. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499397
    4. \n
  4. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499649
    5. \n
  5. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537
    6. \n
  6. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537
    7. \n
\n

Playground Time Series Forecasting challenges

\n

Season3-Episode 20

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ambrosm/pss3e20-eda-which-makes-sense
    2. \n
  2. https://www.kaggle.com/code/kacperrabczewski/rwanda-co2-step-by-step-guide
    3. \n
  3. https://www.kaggle.com/code/yaaangzhou/pg-s3-e20-eda-modeling
    4. \n
  4. https://www.kaggle.com/code/dmitryuarov/ps3e20-rwanda-emission-advanced-fe-20-88
    5. \n
  5. https://www.kaggle.com/code/iqbalsyahakbar/ps3e20-time-series-for-beginners
    6. \n
\n

Season3-Episode 19

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/tumpanjawat/s3e19-course-eda-fe-lightgbm
    2. \n
  2. https://www.kaggle.com/code/iqbalsyahakbar/ps3e19-time-series-for-beginners
    3. \n
  3. https://www.kaggle.com/code/ivyzang/1st-place-solution-less-is-more
    4. \n
  4. https://www.kaggle.com/code/tetsutani/ps3e19-eda-ensemble-ml-pipeline-rnn-by-skorch
    5. \n
  5. https://www.kaggle.com/code/kacperrabczewski/last-minute-forecasting
    6. \n
\n

TPS- September2022

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/azminetoushikwasi/time-series-analysis-forecasting
    2. \n
  2. https://www.kaggle.com/code/cabaxiom/tps-sep-22-eda-and-linear-regression-baseline
    3. \n
  3. https://www.kaggle.com/code/khashayarrahimi94/why-you-should-not-use-correlation
    4. \n
  4. https://www.kaggle.com/code/vencerlanz09/tps-eda-9-models-explanation
    5. \n
  5. https://www.kaggle.com/code/samuelcortinhas/tps-sept-22-timeseries-analysis
    6. \n
\n

TPS- January2022

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/ambrosm/tpsjan22-03-linear-model
    2. \n
  2. https://www.kaggle.com/code/ambrosm/tpsjan22-01-eda-which-makes-sense
    3. \n
  3. https://www.kaggle.com/code/usharengaraju/tensorflow-tf-data-keraspreprocessinglayers-w-b
    4. \n
  4. https://www.kaggle.com/code/teckmengwong/tps2201-hybrid-time-series
    5. \n
  5. https://www.kaggle.com/code/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex
    6. \n
\n

GoDaddy - Microbusiness Density Forecasting

\n

Kernels- most voted

\n
    \n
  1. https://www.kaggle.com/code/titericz/better-xgb-baseline
    2. \n
  2. https://www.kaggle.com/code/cdeotte/linear-regression-baseline-lb-1-092
    3. \n
  3. https://www.kaggle.com/code/tanmay111999/gdmbf-ar-ma-arma-arima-sarima-auto-arima
    4. \n
  4. https://www.kaggle.com/code/cdeotte/seasonal-model-with-validation-lb-1-091
    5. \n
  5. https://www.kaggle.com/code/kimtaehun/complete-baseline-code-with-various-ml-model
    6. \n
\n

High scoring approaches and discussions-

\n
    \n
  1. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395131 -- rank1
    2. \n
  2. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395264 -- rank2
    3. \n
  3. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/418287 -- rank3
    4. \n
  4. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/394821 -- rank4
    5. \n
\n

Miscellaneous kernel references on time series-

\n
    \n
  1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models
    2. \n
  2. https://www.kaggle.com/code/kanncaa1/time-series-prediction-tutorial-with-eda
    3. \n
  3. https://www.kaggle.com/code/freespirit08/time-series-for-beginners-with-arima
    4. \n
  4. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-prophet
    5. \n
  5. https://www.kaggle.com/code/iamleonie/intro-to-time-series-forecasting
    6. \n
  6. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-machine-learning-yt
    7. \n
  7. https://www.kaggle.com/code/rohanrao/a-modern-time-series-tutorial
    8. \n
  8. https://www.kaggle.com/code/cdeotte/time-series-eda
    9. \n
  9. https://www.kaggle.com/code/janiobachmann/s-p-500-time-series-forecasting-with-prophet
    10. \n
  10. https://www.kaggle.com/code/robikscube/pt2-time-series-forecasting-with-xgboost
    11. \n
\n

Wishing you the best for the assignment and happy learning!

", "rawMarkdown": "Hello all,\n\nAll the best for the time series tabular challenge! Hope the below materials are of use to start off well here. We have a number of time series artefacts for reference here-\n\n#[Child Mind Institute - Detect Sleep States](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states)\n\n## Most voted kernels\n- https://www.kaggle.com/code/tubotubo/cmi-submit\n- https://www.kaggle.com/code/carlmcbrideellis/zzzs-random-forest-model-starter\n- https://www.kaggle.com/code/gvyshnya/to-sleep-or-not-to-sleep-deep-eda-dive\n- https://www.kaggle.com/code/lccburk/feature-engineering-and-random-forest-prediction\n- https://www.kaggle.com/code/carlmcbrideellis/zzzs-make-small-starter-datasets-target\n- https://www.kaggle.com/code/patrick0302/viz-of-sleeping-time-series\n- https://www.kaggle.com/code/werus23/sleep-critical-point-infer\n\n## Top ranked solutions\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459715\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459627\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459599\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459637\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459766\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459604\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459598\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/460372\n\n# [Jane Street Market Prediction](https://www.kaggle.com/competitions/jane-street-market-prediction/overview)\n## Most voted kernels\n- https://www.kaggle.com/code/carlmcbrideellis/jane-street-eda-of-day-0-and-feature-importance\n- https://www.kaggle.com/code/hamditarek/market-prediction-xgboost-with-gpu-fit-in-1min\n- https://www.kaggle.com/code/aimind/bottleneck-encoder-mlp-keras-tuner-8601c5\n- https://www.kaggle.com/code/gogo827jz/jane-street-neural-network-starter\n- https://www.kaggle.com/code/muhammadmelsherbini/jane-street-extensive-eda-pca-starter\n- https://www.kaggle.com/code/tarlannazarov/own-jane-street-with-keras-nn\n- https://www.kaggle.com/code/odins0n/exploring-time-series-plots-beginners-guide\n- https://www.kaggle.com/code/jorijnsmit/found-the-holy-grail-grouptimeseriessplit\n- https://www.kaggle.com/code/snippsy/bottleneck-encoder-mlp-keras-tuner\n- https://www.kaggle.com/code/a763337092/blending-tensorflow-and-pytorch\n\n## Top ranked solutions\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224348 -- rank 1\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224713 -- rank 3\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/226837 -- rank 10\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/269181 -- rank 15\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224079 -- rank 23\n\n# [Jane Street Real-Time Market Data Forecasting](https://www.kaggle.com/competitions/jane-street-market-prediction/overview)\n## Most voted kernels\n\n- https://www.kaggle.com/code/yuanzhezhou/jane-street-baseline-lgb-xgb-and-catboost\n- https://www.kaggle.com/code/allegich/jane-street-time-series-analysis-eda-ensemble\n- https://www.kaggle.com/code/voix97/jane-street-rmf-inference-nn-xgb\n- https://www.kaggle.com/code/motono0223/eda-jane-street-real-time-market-data-forecasting\n- https://www.kaggle.com/code/eivolkova/public-lb-6th\n- https://www.kaggle.com/code/simonedegasperis/online-retrain-poc\n- https://www.kaggle.com/code/ahsuna123/jane-street-24-day-0-eda-and-feature-importance\n- https://www.kaggle.com/code/motono0223/js24-inference-gbdt-with-lags-singlemodel\n\n# Similar Kaggle competition references\n### [ASHRAE - Great Energy Predictor III](https://www.kaggle.com/competitions/ashrae-energy-prediction)\n#### Kernels- top 5 voted \n1. https://www.kaggle.com/code/caesarlupum/ashrae-start-here-a-gentle-introduction\n2. https://www.kaggle.com/code/nroman/eda-for-ashrae\n3. https://www.kaggle.com/code/rohanrao/ashrae-half-and-half\n4. https://www.kaggle.com/code/corochann/optuna-tutorial-for-hyperparameter-optimization\n5. https://www.kaggle.com/code/corochann/ashrae-training-lgbm-by-meter-type\n\n#### Kernels- top 3 scores\n1. https://www.kaggle.com/code/patrick0302/postprocessed-models-bland-by-leak\n2. https://www.kaggle.com/code/vladimirsydor/add-leak\n3. https://www.kaggle.com/code/gpamoukoff/ashrae-subm-stack-fin-3\n\n### High scoring approaches and discussions- \n1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124709 -- rank1\n2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123481 -- rank2\n3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124984 -- rank3\n4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124788 --rank4\n5. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/127086 --rank5\n6. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123525 -- rank9\n\n### Other useful posts and discussions\n1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/112872\n2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/114345\n3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/113678\n4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/115698\n\n## [Optiver- Trading at the Close](https://www.kaggle.com/competitions/optiver-trading-at-the-close)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models\n2. https://www.kaggle.com/code/yuanzhezhou/baseline-lgb-xgb-and-catboost\n3. https://www.kaggle.com/code/a27182818/explain-the-data-lightgbm-baseline\n4. https://www.kaggle.com/code/lblhandsome/optiver-robust-best-single-model\n5. https://www.kaggle.com/code/verracodeguacas/fold-cv\n6. https://www.kaggle.com/code/peizhengwang/best-public-score\n7. https://www.kaggle.com/code/siddhvr/optiver-trading-at-the-close-sub\n\n### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/487446\n2. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486868\n3. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/462653\n4. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486086\n\n## [Enefit - Predict Energy Behavior of Prosumers](https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/rafiko1/enefit-xgboost-starter\n2. https://www.kaggle.com/code/vitalykudelya/explain-dataset-and-baseline\n3. https://www.kaggle.com/code/vincentschuler/enefit-baseline-cross-validation\n4. https://www.kaggle.com/code/greysky/enefit-generic-notebook\n5. https://www.kaggle.com/code/vitalykudelya/enefit-target-diff\n6. https://www.kaggle.com/code/ahmedabdulwahab/pandas-data-description-and-starters-guide\n\n### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472793\n2. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499938\n3. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499397\n4. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499649\n5. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537\n6. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537\n\n## Playground Time Series Forecasting challenges\n### [Season3-Episode 20](https://www.kaggle.com/competitions/playground-series-s3e20)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ambrosm/pss3e20-eda-which-makes-sense\n2. https://www.kaggle.com/code/kacperrabczewski/rwanda-co2-step-by-step-guide\n3. https://www.kaggle.com/code/yaaangzhou/pg-s3-e20-eda-modeling\n4. https://www.kaggle.com/code/dmitryuarov/ps3e20-rwanda-emission-advanced-fe-20-88\n5. https://www.kaggle.com/code/iqbalsyahakbar/ps3e20-time-series-for-beginners\n\n### [Season3-Episode 19](https://www.kaggle.com/competitions/playground-series-s3e19)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/tumpanjawat/s3e19-course-eda-fe-lightgbm\n2. https://www.kaggle.com/code/iqbalsyahakbar/ps3e19-time-series-for-beginners\n3. https://www.kaggle.com/code/ivyzang/1st-place-solution-less-is-more\n4. https://www.kaggle.com/code/tetsutani/ps3e19-eda-ensemble-ml-pipeline-rnn-by-skorch\n5. https://www.kaggle.com/code/kacperrabczewski/last-minute-forecasting\n\n### [TPS- September2022](https://www.kaggle.com/competitions/tabular-playground-series-sep-2022)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/azminetoushikwasi/time-series-analysis-forecasting\n2. https://www.kaggle.com/code/cabaxiom/tps-sep-22-eda-and-linear-regression-baseline\n3. https://www.kaggle.com/code/khashayarrahimi94/why-you-should-not-use-correlation\n4. https://www.kaggle.com/code/vencerlanz09/tps-eda-9-models-explanation\n5. https://www.kaggle.com/code/samuelcortinhas/tps-sept-22-timeseries-analysis\n\n### [TPS- January2022](https://www.kaggle.com/competitions/tabular-playground-series-jan-2022)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ambrosm/tpsjan22-03-linear-model\n2. https://www.kaggle.com/code/ambrosm/tpsjan22-01-eda-which-makes-sense\n3. https://www.kaggle.com/code/usharengaraju/tensorflow-tf-data-keraspreprocessinglayers-w-b\n4. https://www.kaggle.com/code/teckmengwong/tps2201-hybrid-time-series\n5. https://www.kaggle.com/code/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex\n\n## [GoDaddy - Microbusiness Density Forecasting](https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/overview)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/titericz/better-xgb-baseline\n2. https://www.kaggle.com/code/cdeotte/linear-regression-baseline-lb-1-092\n3. https://www.kaggle.com/code/tanmay111999/gdmbf-ar-ma-arma-arima-sarima-auto-arima\n4. https://www.kaggle.com/code/cdeotte/seasonal-model-with-validation-lb-1-091\n5. https://www.kaggle.com/code/kimtaehun/complete-baseline-code-with-various-ml-model\n\n#### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395131 -- rank1\n2. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395264 -- rank2\n3. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/418287 -- rank3\n4. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/394821 -- rank4\n\n## Miscellaneous kernel references on time series- \n1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models\n2. https://www.kaggle.com/code/kanncaa1/time-series-prediction-tutorial-with-eda\n3. https://www.kaggle.com/code/freespirit08/time-series-for-beginners-with-arima\n4. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-prophet\n5. https://www.kaggle.com/code/iamleonie/intro-to-time-series-forecasting\n6. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-machine-learning-yt\n7. https://www.kaggle.com/code/rohanrao/a-modern-time-series-tutorial\n8. https://www.kaggle.com/code/cdeotte/time-series-eda\n9. https://www.kaggle.com/code/janiobachmann/s-p-500-time-series-forecasting-with-prophet\n10. https://www.kaggle.com/code/robikscube/pt2-time-series-forecasting-with-xgboost\n\nWishing you the best for the assignment and happy learning!", "votes": null }, { "id": "3214201", "postDate": "05/31/2025 05:20:33", "content": "

Thanks, of sharing. Could you please recommend some resources for learning Time Series Analysis also? @ravi20076

", "rawMarkdown": "Thanks, of sharing. Could you please recommend some resources for learning Time Series Analysis also? @ravi20076", "votes": null }, { "id": "3214255", "postDate": "05/31/2025 07:08:32", "content": "

These are the ones for time series @sayyedfarrukhmehmood

", "rawMarkdown": "These are the ones for time series @sayyedfarrukhmehmood", "votes": null } ], "comments": [ { "id": 3214201, "author_name": "sayyedfarrukhmehmood", "author_url": "", "post_date": "05/31/2025 05:20:33", "content": "

Thanks, of sharing. Could you please recommend some resources for learning Time Series Analysis also? @ravi20076

", "votes": null, "replies": [ { "id": 3214255, "author_name": "ravi20076", "author_url": "", "post_date": "05/31/2025 07:08:32", "content": "

These are the ones for time series @sayyedfarrukhmehmood

", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "3213547": "Hello all,\n\nAll the best for the time series tabular challenge! Hope the below materials are of use to start off well here. We have a number of time series artefacts for reference here-\n\n#[Child Mind Institute - Detect Sleep States](https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states)\n\n## Most voted kernels\n- https://www.kaggle.com/code/tubotubo/cmi-submit\n- https://www.kaggle.com/code/carlmcbrideellis/zzzs-random-forest-model-starter\n- https://www.kaggle.com/code/gvyshnya/to-sleep-or-not-to-sleep-deep-eda-dive\n- https://www.kaggle.com/code/lccburk/feature-engineering-and-random-forest-prediction\n- https://www.kaggle.com/code/carlmcbrideellis/zzzs-make-small-starter-datasets-target\n- https://www.kaggle.com/code/patrick0302/viz-of-sleeping-time-series\n- https://www.kaggle.com/code/werus23/sleep-critical-point-infer\n\n## Top ranked solutions\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459715\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459627\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459599\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459637\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459766\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459604\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/459598\n- https://www.kaggle.com/competitions/child-mind-institute-detect-sleep-states/discussion/460372\n\n# [Jane Street Market Prediction](https://www.kaggle.com/competitions/jane-street-market-prediction/overview)\n## Most voted kernels\n- https://www.kaggle.com/code/carlmcbrideellis/jane-street-eda-of-day-0-and-feature-importance\n- https://www.kaggle.com/code/hamditarek/market-prediction-xgboost-with-gpu-fit-in-1min\n- https://www.kaggle.com/code/aimind/bottleneck-encoder-mlp-keras-tuner-8601c5\n- https://www.kaggle.com/code/gogo827jz/jane-street-neural-network-starter\n- https://www.kaggle.com/code/muhammadmelsherbini/jane-street-extensive-eda-pca-starter\n- https://www.kaggle.com/code/tarlannazarov/own-jane-street-with-keras-nn\n- https://www.kaggle.com/code/odins0n/exploring-time-series-plots-beginners-guide\n- https://www.kaggle.com/code/jorijnsmit/found-the-holy-grail-grouptimeseriessplit\n- https://www.kaggle.com/code/snippsy/bottleneck-encoder-mlp-keras-tuner\n- https://www.kaggle.com/code/a763337092/blending-tensorflow-and-pytorch\n\n## Top ranked solutions\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224348 -- rank 1\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224713 -- rank 3\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/226837 -- rank 10\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/269181 -- rank 15\n- https://www.kaggle.com/competitions/jane-street-market-prediction/discussion/224079 -- rank 23\n\n# [Jane Street Real-Time Market Data Forecasting](https://www.kaggle.com/competitions/jane-street-market-prediction/overview)\n## Most voted kernels\n\n- https://www.kaggle.com/code/yuanzhezhou/jane-street-baseline-lgb-xgb-and-catboost\n- https://www.kaggle.com/code/allegich/jane-street-time-series-analysis-eda-ensemble\n- https://www.kaggle.com/code/voix97/jane-street-rmf-inference-nn-xgb\n- https://www.kaggle.com/code/motono0223/eda-jane-street-real-time-market-data-forecasting\n- https://www.kaggle.com/code/eivolkova/public-lb-6th\n- https://www.kaggle.com/code/simonedegasperis/online-retrain-poc\n- https://www.kaggle.com/code/ahsuna123/jane-street-24-day-0-eda-and-feature-importance\n- https://www.kaggle.com/code/motono0223/js24-inference-gbdt-with-lags-singlemodel\n\n# Similar Kaggle competition references\n### [ASHRAE - Great Energy Predictor III](https://www.kaggle.com/competitions/ashrae-energy-prediction)\n#### Kernels- top 5 voted \n1. https://www.kaggle.com/code/caesarlupum/ashrae-start-here-a-gentle-introduction\n2. https://www.kaggle.com/code/nroman/eda-for-ashrae\n3. https://www.kaggle.com/code/rohanrao/ashrae-half-and-half\n4. https://www.kaggle.com/code/corochann/optuna-tutorial-for-hyperparameter-optimization\n5. https://www.kaggle.com/code/corochann/ashrae-training-lgbm-by-meter-type\n\n#### Kernels- top 3 scores\n1. https://www.kaggle.com/code/patrick0302/postprocessed-models-bland-by-leak\n2. https://www.kaggle.com/code/vladimirsydor/add-leak\n3. https://www.kaggle.com/code/gpamoukoff/ashrae-subm-stack-fin-3\n\n### High scoring approaches and discussions- \n1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124709 -- rank1\n2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123481 -- rank2\n3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124984 -- rank3\n4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/124788 --rank4\n5. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/127086 --rank5\n6. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/123525 -- rank9\n\n### Other useful posts and discussions\n1. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/112872\n2. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/114345\n3. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/113678\n4. https://www.kaggle.com/competitions/ashrae-energy-prediction/discussion/115698\n\n## [Optiver- Trading at the Close](https://www.kaggle.com/competitions/optiver-trading-at-the-close)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models\n2. https://www.kaggle.com/code/yuanzhezhou/baseline-lgb-xgb-and-catboost\n3. https://www.kaggle.com/code/a27182818/explain-the-data-lightgbm-baseline\n4. https://www.kaggle.com/code/lblhandsome/optiver-robust-best-single-model\n5. https://www.kaggle.com/code/verracodeguacas/fold-cv\n6. https://www.kaggle.com/code/peizhengwang/best-public-score\n7. https://www.kaggle.com/code/siddhvr/optiver-trading-at-the-close-sub\n\n### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/487446\n2. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486868\n3. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/462653\n4. https://www.kaggle.com/competitions/optiver-trading-at-the-close/discussion/486086\n\n## [Enefit - Predict Energy Behavior of Prosumers](https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/rafiko1/enefit-xgboost-starter\n2. https://www.kaggle.com/code/vitalykudelya/explain-dataset-and-baseline\n3. https://www.kaggle.com/code/vincentschuler/enefit-baseline-cross-validation\n4. https://www.kaggle.com/code/greysky/enefit-generic-notebook\n5. https://www.kaggle.com/code/vitalykudelya/enefit-target-diff\n6. https://www.kaggle.com/code/ahmedabdulwahab/pandas-data-description-and-starters-guide\n\n### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472793\n2. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499938\n3. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499397\n4. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/499649\n5. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537\n6. https://www.kaggle.com/competitions/predict-energy-behavior-of-prosumers/discussion/472537\n\n## Playground Time Series Forecasting challenges\n### [Season3-Episode 20](https://www.kaggle.com/competitions/playground-series-s3e20)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ambrosm/pss3e20-eda-which-makes-sense\n2. https://www.kaggle.com/code/kacperrabczewski/rwanda-co2-step-by-step-guide\n3. https://www.kaggle.com/code/yaaangzhou/pg-s3-e20-eda-modeling\n4. https://www.kaggle.com/code/dmitryuarov/ps3e20-rwanda-emission-advanced-fe-20-88\n5. https://www.kaggle.com/code/iqbalsyahakbar/ps3e20-time-series-for-beginners\n\n### [Season3-Episode 19](https://www.kaggle.com/competitions/playground-series-s3e19)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/tumpanjawat/s3e19-course-eda-fe-lightgbm\n2. https://www.kaggle.com/code/iqbalsyahakbar/ps3e19-time-series-for-beginners\n3. https://www.kaggle.com/code/ivyzang/1st-place-solution-less-is-more\n4. https://www.kaggle.com/code/tetsutani/ps3e19-eda-ensemble-ml-pipeline-rnn-by-skorch\n5. https://www.kaggle.com/code/kacperrabczewski/last-minute-forecasting\n\n### [TPS- September2022](https://www.kaggle.com/competitions/tabular-playground-series-sep-2022)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/azminetoushikwasi/time-series-analysis-forecasting\n2. https://www.kaggle.com/code/cabaxiom/tps-sep-22-eda-and-linear-regression-baseline\n3. https://www.kaggle.com/code/khashayarrahimi94/why-you-should-not-use-correlation\n4. https://www.kaggle.com/code/vencerlanz09/tps-eda-9-models-explanation\n5. https://www.kaggle.com/code/samuelcortinhas/tps-sept-22-timeseries-analysis\n\n### [TPS- January2022](https://www.kaggle.com/competitions/tabular-playground-series-jan-2022)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/ambrosm/tpsjan22-03-linear-model\n2. https://www.kaggle.com/code/ambrosm/tpsjan22-01-eda-which-makes-sense\n3. https://www.kaggle.com/code/usharengaraju/tensorflow-tf-data-keraspreprocessinglayers-w-b\n4. https://www.kaggle.com/code/teckmengwong/tps2201-hybrid-time-series\n5. https://www.kaggle.com/code/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex\n\n## [GoDaddy - Microbusiness Density Forecasting](https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/overview)\n#### Kernels- most voted \n1. https://www.kaggle.com/code/titericz/better-xgb-baseline\n2. https://www.kaggle.com/code/cdeotte/linear-regression-baseline-lb-1-092\n3. https://www.kaggle.com/code/tanmay111999/gdmbf-ar-ma-arma-arima-sarima-auto-arima\n4. https://www.kaggle.com/code/cdeotte/seasonal-model-with-validation-lb-1-091\n5. https://www.kaggle.com/code/kimtaehun/complete-baseline-code-with-various-ml-model\n\n#### High scoring approaches and discussions-\n1. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395131 -- rank1\n2. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/395264 -- rank2\n3. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/418287 -- rank3\n4. https://www.kaggle.com/competitions/godaddy-microbusiness-density-forecasting/discussion/394821 -- rank4\n\n## Miscellaneous kernel references on time series- \n1. https://www.kaggle.com/code/ravi20076/optiver-baseline-models\n2. https://www.kaggle.com/code/kanncaa1/time-series-prediction-tutorial-with-eda\n3. https://www.kaggle.com/code/freespirit08/time-series-for-beginners-with-arima\n4. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-prophet\n5. https://www.kaggle.com/code/iamleonie/intro-to-time-series-forecasting\n6. https://www.kaggle.com/code/robikscube/time-series-forecasting-with-machine-learning-yt\n7. https://www.kaggle.com/code/rohanrao/a-modern-time-series-tutorial\n8. https://www.kaggle.com/code/cdeotte/time-series-eda\n9. https://www.kaggle.com/code/janiobachmann/s-p-500-time-series-forecasting-with-prophet\n10. https://www.kaggle.com/code/robikscube/pt2-time-series-forecasting-with-xgboost\n\nWishing you the best for the assignment and happy learning!", "3214201": "Thanks, of sharing. Could you please recommend some resources for learning Time Series Analysis also? @ravi20076", "3214255": "These are the ones for time series @sayyedfarrukhmehmood" }, "source": "meta" }