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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
| Date | Stars |
|---|---|
| 2026-07-24 | 1364 |
| 2026-07-25 | 1364 |
| 2026-07-28 | 1364 |
| 2026-07-30 | 1364 |
| 2026-07-31 | 1367 |
| 2026-08-06 | 1372 |
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This week
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# Must Read Papers for Data Science, ML, and DL ### Curated collection of Data Science, Machine Learning and Deep Learning papers, reviews and articles that are on must read list. --- > NOTE: :construction: in process of updating, let me know what additional papers, articles, blogs to add I will add them here. ### How to use > :point_right: :star: this repo ## Contributing - :point_right: :arrows_clockwise: Please feel free to [Submit Pull Request](https://github.com/hurshd0/must-read-papers-for-ml/pulls), if links are broken, or I am missing any important papers, blogs or articles. [](https://github.com/hurshd0/must-read-papers-for-ml/graphs/commit-activity) ### :point_down: READ THIS :point_down: - :point_right: Reading paper with heavy math is hard, it takes time and effort to understand, most of it is dedication and motivation to not quit, don't be discouraged, read once, read twice, read thrice,... until it clicks and blows you away. :1st_place_medal: - Read it first :2nd_place_medal: - Read it second :3rd_place_medal: - Read it third --- ## Data Science ### :bar_chart: Pre-processing & EDA :1st_place_medal: :page_facing_up:[Data preprocessing - Tidy data - by Hadley Wickham](https://vita.had.co.nz/papers/tidy-data.pdf) ### :notebook: General DS :1st_place_medal: :page_facing_up: [Statistical Modeling: The Two Cultures - by Leo Breiman](https://projecteuclid.org/download/pdf_1/euclid.ss/1009213726) :2nd_place_medal: :page_facing_up: [A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning](https://arxiv.org/pdf/1908.01755.pdf) - :video_camera: [KDD 2019 Cynthia Rudin's Keynote](https://youtu.be/wL4X4lG20sM) :1st_place_medal: :page_facing_up: [Frequentism and Bayesianism: A Python-driven Primer by Jake VanderPlas](https://arxiv.org/pdf/1411.5018.pdf) --- ## Machine Learning ### :dart: General ML :1st_place_medal: :page_facing_up: [Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning - by Sebastian Raschka](https://arxiv.org/pdf/1811.12808.pdf) :1st_place_medal: :page_facing_up: [A Brief Introduction into Machine Learning - by Gunnar Ratsch](https://events.ccc.de/congress/2004/fahrplan/files/105-machine-learning-paper.pdf) :3rd_place_medal: :page_facing_up: [An Introduction to the Conjugate Gradient Method Without the Agonizing Pain - by Jonathan Richard Shewchuk](http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf) :3rd_place_medal: :page_facing_up: [On Model Stability as a Function of Random Seed](https://arxiv.org/pdf/1909.10447) ### :mag: Outlier/Anomaly detection :1st_place_medal: :newspaper: [Outlier Detection : A Survey](https://pdfs.semanticscholar.org/912b/0b7879ca99bf654a26bbb0d50d4b8e0ed6c0.pdf) ### :rocket: Boosting :2nd_place_medal: :page_facing_up: [XGBoost: A Scalable Tree Boosting System](https://arxiv.org/pdf/1603.02754.pdf) :2nd_place_medal: :page_facing_up: [LightGBM: A Highly Efficient Gradient BoostingDecision Tree](https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf) :2nd_place_medal: :page_facing_up: [AdaBoost and the Super Bowl of Classifiers - A Tutorial Introduction to Adaptive Boosting](http://www.inf.fu-berlin.de/inst/ag-ki/adaboost4.pdf) :3rd_place_medal: :page_facing_up: [Greedy Function Approximation: A Gradient Boosting Machine](https://projecteuclid.org/download/pdf_1/euclid.aos/1013203451) ### :book: Unraveling Blackbox ML :3rd_place_medal: :page_facing_up: [Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation](https://arxiv.org/pdf/1309.6392.pdf) :3rd_place_medal: :page_facing_up: [Data Shapley: Equitable Valuation of Data for Machine Learning](https://arxiv.org/pdf/1904.02868.pdf) ### :scissors: Dimensionality Reduction :1st_place_medal: :page_facing_up: [A Tutorial o
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matched fp:6bf361b2f2bcfb7b, topic:papers, readme:tutorial
matched fp:6bf361b2f2bcfb7b, topic:deep-learning