eugeneyan/applied-ml

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Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ [](./CONTRIBUTING.md) [](https://twitter.com/eugeneyan/status/1350509546133811200) Figuring out how to implement your ML project? Learn how other organizations did it: P.S., Want a summary of ML advancements? 👉ml-surveys P.P.S,…

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Read the full README ↗ · Preview checked 2026-11-01T08:03:33.341Z

Inside the original README — Document outline
  1. applied-ml
  2. Data Quality
  3. Data Engineering
  4. Data Discovery
  5. Feature Stores
  6. Classification
  7. Regression
  8. Forecasting
  9. Recommendation
  10. Search & Ranking
  11. Embeddings
  12. Natural Language Processing

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Documentation belongs to its respective authors. Reported project/model license: MIT. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

What this repository does

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Repository facts

Owner
eugeneyan
Primary language
Not reported
Stars
30,755
Forks
4,050
Open issues + pull requests
12
License
MIT
Archived
No
Default branch
main
Created
2020-07-04T18:57:47.000Z
Last push
2024-07-18T22:41:02.000Z

Topics and intended use

Owner-supplied topics: applied-data-science, applied-machine-learning, computer-vision, data-discovery, data-engineering, data-quality, data-science, deep-learning, machine-learning, natural-language-processing, production, recsys, reinforcement-learning, search

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