{ "id": 371374, "title": "Good Beginner Notebooks ", "url": "/competitions/emsi-5iir-ds/discussion/371374", "author_name": "", "post_date": "2022-12-09T14:46:27.939375900Z", "votes": 8, "comment_count": 2, "views": 0, "content": "
\n
    \n

  1. Catboost with EDA and feature selection by @lszlbebesi

    2. \n

  2. Logistic + RF + LGBM by @srivnaman

    3. \n

  3. XGB+ FE by @rogeriodelfim

    4. \n

  4. Pytorch + GPU by @matthewszhang

    5. \n

  5. FastAI by @mukeshrajmahendran

    6. \n

  6. TPS-May-22 Tensorflow Decision Forests by @arnavr10880

    7. \n

  7. Logistic regression by @ninjaac

    8. \n

  8. Advanced Keras by @ambrosm

    9. \n

  9. FlaML by @gavisr

    10. \n

  10. Pycaret by @wasshoiwasshoi

    11. \n
\n

Taken from a post on the Tabular Playground Series - May 2022 discussion board

\n
", "messages": [ { "id": "2060102", "postDate": "12/09/2022 14:46:27", "content": "
\n
    \n

  1. Catboost with EDA and feature selection by @lszlbebesi

    2. \n

  2. Logistic + RF + LGBM by @srivnaman

    3. \n

  3. XGB+ FE by @rogeriodelfim

    4. \n

  4. Pytorch + GPU by @matthewszhang

    5. \n

  5. FastAI by @mukeshrajmahendran

    6. \n

  6. TPS-May-22 Tensorflow Decision Forests by @arnavr10880

    7. \n

  7. Logistic regression by @ninjaac

    8. \n

  8. Advanced Keras by @ambrosm

    9. \n

  9. FlaML by @gavisr

    10. \n

  10. Pycaret by @wasshoiwasshoi

    11. \n
\n

Taken from a post on the Tabular Playground Series - May 2022 discussion board

\n
", "rawMarkdown": "> 1. [Catboost with EDA and feature selection](https://www.kaggle.com/code/lszlbebesi/catboost-with-eda-and-feature-selection) by @lszlbebesi\n> \n> 2. [Logistic + RF + LGBM](https://www.kaggle.com/code/srivnaman/logistic-rf-lightgbm) by @srivnaman\n> \n> 3. [XGB+ FE](https://www.kaggle.com/code/rogeriodelfim/tps-may-2021-02-xgb-feature-engineering) by @rogeriodelfim\n> \n> 4. [Pytorch + GPU](https://www.kaggle.com/code/matthewszhang/tps-may-pytorch-with-gpu) by @matthewszhang\n> \n> 5. [FastAI](https://www.kaggle.com/code/mukeshrajm/tabular-may-using-fastai-work-in-progress) by @mukeshrajmahendran \n> \n> 6. [TPS-May-22 Tensorflow Decision Forests](https://www.kaggle.com/code/arnavr10880/tps-may-22-tensorflow-decision-forests) by @arnavr10880\n> \n> 7. [Logistic regression](https://www.kaggle.com/code/ninjaac/tpsmay22-logestic-reg-all-you-need-to-know) by @ninjaac\n> \n> 8. [Advanced Keras](https://www.kaggle.com/code/ambrosm/tpsmay22-advanced-keras) by @ambrosm\n> \n> 9. [FlaML](https://www.kaggle.com/code/gavisr/baseline-with-fast-automl-flaml) by @gavisr\n> \n> 10. [Pycaret](https://www.kaggle.com/code/wasshoiwasshoi/tps-2022-may-with-automl-pycaret1) by @wasshoiwasshoi\n>\nTaken from a post on the Tabular Playground Series - May 2022 discussion board", "votes": null }, { "id": "2061298", "postDate": "12/10/2022 23:40:29", "content": "

thank you that is so helpful 👍👌

", "rawMarkdown": "thank you that is so helpful 👍👌", "votes": null }, { "id": "2068093", "postDate": "12/17/2022 13:48:11", "content": "

free real estate

", "rawMarkdown": "free real estate", "votes": null } ], "comments": [ { "id": 2061298, "author_name": "hatimchifa", "author_url": "", "post_date": "12/10/2022 23:40:29", "content": "

thank you that is so helpful 👍👌

", "votes": null, "replies": [] }, { "id": 2068093, "author_name": "abdellahkadem", "author_url": "", "post_date": "12/17/2022 13:48:11", "content": "

free real estate

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2060102": "> 1. [Catboost with EDA and feature selection](https://www.kaggle.com/code/lszlbebesi/catboost-with-eda-and-feature-selection) by @lszlbebesi\n> \n> 2. [Logistic + RF + LGBM](https://www.kaggle.com/code/srivnaman/logistic-rf-lightgbm) by @srivnaman\n> \n> 3. [XGB+ FE](https://www.kaggle.com/code/rogeriodelfim/tps-may-2021-02-xgb-feature-engineering) by @rogeriodelfim\n> \n> 4. [Pytorch + GPU](https://www.kaggle.com/code/matthewszhang/tps-may-pytorch-with-gpu) by @matthewszhang\n> \n> 5. [FastAI](https://www.kaggle.com/code/mukeshrajm/tabular-may-using-fastai-work-in-progress) by @mukeshrajmahendran \n> \n> 6. [TPS-May-22 Tensorflow Decision Forests](https://www.kaggle.com/code/arnavr10880/tps-may-22-tensorflow-decision-forests) by @arnavr10880\n> \n> 7. [Logistic regression](https://www.kaggle.com/code/ninjaac/tpsmay22-logestic-reg-all-you-need-to-know) by @ninjaac\n> \n> 8. [Advanced Keras](https://www.kaggle.com/code/ambrosm/tpsmay22-advanced-keras) by @ambrosm\n> \n> 9. [FlaML](https://www.kaggle.com/code/gavisr/baseline-with-fast-automl-flaml) by @gavisr\n> \n> 10. [Pycaret](https://www.kaggle.com/code/wasshoiwasshoi/tps-2022-may-with-automl-pycaret1) by @wasshoiwasshoi\n>\nTaken from a post on the Tabular Playground Series - May 2022 discussion board", "2061298": "thank you that is so helpful 👍👌", "2068093": "free real estate" }, "source": "meta" }