https://github.com/valeman/awesome_catboost
The repository to showcase the best framework for tabular data - the Awesome CatBoost
https://github.com/valeman/awesome_catboost
List: awesome_catboost
Last synced: 10 months ago
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The repository to showcase the best framework for tabular data - the Awesome CatBoost
- Host: GitHub
- URL: https://github.com/valeman/awesome_catboost
- Owner: valeman
- Created: 2024-02-25T12:42:12.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-11T16:01:04.000Z (about 1 year ago)
- Last Synced: 2025-03-13T04:01:45.974Z (10 months ago)
- Size: 1.43 MB
- Stars: 227
- Watchers: 7
- Forks: 24
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome_catboost - The repository to showcase the best framework for tabular data - the Awesome CatBoost. (Other Lists / TeX Lists)
README
# Awesome_CatBoost
**π₯ CatBoost: The Unrivaled King of Tabular Data π₯**
**TL;DR:** CatBoost isn't just another machine learning frameworkβit's THE framework dominating the tabular data landscape. And weβve got the proof. π
π‘ **Why CatBoost Rules:**
- According to **"A Closer Look at Deep Learning on Tabular Data"**, the **largest-ever study** (300 datasets!) on tabular data, CatBoost consistently outperforms both deep learning and traditional tree-based models.
- Seamlessly handles categorical features nativelyβno more preprocessing headaches.
- Built for efficiency, accuracy, and real-world practicality.
π **Explore the Ultimate Resource**
The **[Awesome CatBoost Repository](https://github.com/valeman/Awesome_CatBoost)** is your one-stop shop to master this powerhouse. Tutorials, best practices, cutting-edge papers, and moreβall in one place.
π Tabular data is everywhere, and CatBoost proves itβs the ultimate solution. Time to level up your machine learning game. πͺ
π Dive in now: [Awesome CatBoost Repo](https://github.com/valeman/Awesome_CatBoost)
π Read the groundbreaking paper: [ArXiv Study](https://arxiv.org/abs/2407.00956)
#MachineLearning #CatBoost #DataScience #AI #TabularData #GradientBoosting #AwesomeRepo #Domination
## [Table of Contents]()
* [Events](#events)
* [Books](#books)
* [PhD and MSc Theses](#theses)
* [Videos](#videos)
* [Papers](#papers)
* [Papers Time Series](#papers-time-series)
* [Articles](#articles)
* [Kaggle](#kaggle)
* [Tutorials](#tutorials)
* [Courses](#courses)
* [Presentation_slides](#presentation-slides)
* [Researchers](#researchers)
* [Websites](#websites)
* [Twitter](#twitter)
* [TikTok](#tiktok)
* [Conferences](#conferences)
* [Python](#python)
* [R](#r)
* [Julia](#julia)
* [Other Languages](#other-languages)
* [AI platforms](#ai-platforms)
* [Patents](#patents)
* [Miscellaneous](#miscellaneous)
* [Contributing](#contributing)
## Videos
1. [Anna Veronika Dorogush - CatBoost - the new generation of Gradient Boosting](https://www.youtube.com/watch?v=oGRIGdsz7bM) (EuroPython Conference, 2018)
2. [XGBoost β LightGBM β CatBoost β Scikit-Learn GRADIENT BOOSTING Performance Compared](https://www.youtube.com/watch?v=yO6gJM_t1Bw)
3. [Yandex Catboost: Open-source Gradient Boosting Library](https://www.youtube.com/watch?v=s8Q_orF4tcI) (2018)
4. [CatBoost Part 1: Ordered Target Encoding](https://www.youtube.com/watch?v=KXOTSkPL2X4) by Josh Starmer (2023)
## Papers
1. [A Closer Look at Deep Learning on Tabular Data](https://arxiv.org/abs/2407.00956) large scale study (300! datasets) showing CatBoost dominates on tabular data π₯π₯π₯π₯π₯πππππ [code](https://github.com/qile2000/LAMDA-TALENT)
2. [CatBoost: gradient boosting with categorical features support](http://learningsys.org/nips17/assets/papers/paper_11.pdf) by Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin (NeurIPS, 2017) π₯π₯π₯π₯π₯
3. [CatBoost: unbiased boosting with categorical features](https://arxiv.org/abs/1706.09516) by Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin (Neurips, 2018) π₯π₯π₯π₯π₯
4. [KiDS-SQuaD. Machine learning selection of bright extragalactic objects to search for new gravitationally lensed quasars](https://www.aanda.org/articles/aa/full_html/2019/12/aa36006-19/aa36006-19.html) (2019)
5. [When Do Neural Nets Outperform Boosted Trees on Tabular Data?](https://arxiv.org/pdf/2305.02997v3.pdf) (2023) large scale study showing CatBoost outperofmed xgboost by 6% in terms of accuracy π₯π₯π₯π₯π₯
6. [CatBoost for big data: an interdisciplinary review](CatBoost for big data: an interdisciplinary review) (2020) π₯π₯π₯π₯π₯
7. [A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets](https://arxiv.org/abs/2408.14817) (2024) π₯π₯π₯π₯π₯ large scale study showing CatBoost dominates on tabular data
## Articles
1. [The Gradient Boosters V: CatBoost](https://deep-and-shallow.com/2020/02/29/the-gradient-boosters-v-catboost/) by Manu Joseph (2020)
2. [CatBoost Hyperparameter Tuning Guide with Optuna](https://forecastegy.com/posts/catboost-hyperparameter-tuning-guide-with-optuna/) by Kaggle Grandmaster Mario Filho (2023) π₯π₯π₯π₯π₯
3. [XGBoost? CatBoost? LightGBM?](https://www.joinplank.com/articles/xgboost-catboost-lightgbm) (2023)
4. [Stop Using XGBoostβ¦](https://towardsdatascience.com/stop-using-xgboost-660ed6718845) by Matt Przybyla (2021)
5. [When to Choose CatBoost Over XGBoost or LightGBM - Practical Guide](https://neptune.ai/blog/when-to-choose-catboost-over-xgboost-or-lightgbm) (2023)
6. [CatBoost vs. Light GBM vs. XGBoost](https://www.kdnuggets.com/2018/03/catboost-vs-light-gbm-vs-xgboost.html)
7. [CatBoost: Gradient Tree Boosting for Recommender Systems, Classification and Regression](https://towardsdatascience.com/catboost-gradient-tree-boosting-for-recommender-systems-classification-and-regression-2f04f573a79e)
8. [Is CatBoost faster than LightGBM and XGBoost?](https://tech.deliveryhero.com/is-catboost-faster-than-lightgbm-and-xgboost/)https://tech.deliveryhero.com/is-catboost-faster-than-lightgbm-and-xgboost/)
9. [5 Cute Features of CatBoost - Other boosting algorithms don't have these features](https://towardsdatascience.com/5-cute-features-of-catboost-61532c260f69) by Rukshan Pramoditha (2021)
10. [What Is CatBoost?](https://builtin.com/machine-learning/catboost#) by Artem Oppermann (2023)
11. [CatBoost Secrets: How It Handles Categorical Columns and Tree Growth](https://medium.com/@gneyapandya1234/catboost-secrets-how-it-handles-categorical-columns-and-tree-growth-b2ae9b96284b) by Gneya Pandya (2024)
12. [Why you should learn CatBoost now](https://towardsdatascience.com/why-you-should-learn-catboost-now-390fb3895f76) by Felix Revert (2020)
13. [How CatBoost encodes categorical variables?](https://towardsdatascience.com/how-catboost-encodes-categorical-variables-3866fb2ae640) by Adrian Biarnes (2021)
## Kaggle
1. [catboost uncertainty](https://www.kaggle.com/code/raddar/catboost-uncertainty) by x4 Kaggle Grandmaster Darius BaruΕ‘auskas (Kaggle 'raddar') (2024) π₯π₯π₯π₯π₯