Refolk

Top Data science repositories on GitHub

Notebooks, analysis libraries, and data tooling.

Ranked by stars across 2,480 repositories tagged data-science. Refreshed daily.

  1. 1
    microsoft/ML-For-Beginners90,739 · ⑂ 22,369

    12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

    • ml
    • data-science
    • machine-learning
    • machine-learning-algorithms
    • machinelearning
    • python
  2. 2
    apache/superset74,847 · ⑂ 18,355

    Apache Superset is a Data Visualization and Data Exploration Platform

    • superset
    • apache
    • apache-superset
    • data-visualization
    • data-viz
    • analytics
  3. 3
    Asabeneh/30-Days-Of-Python74,181 · ⑂ 13,535

    The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

    • 30-days-of-python
    • python
    • flask
    • github
    • heroku
    • matplotlib
  4. 4
    scikit-learn/scikit-learn67,319 · ⑂ 27,425

    scikit-learn: machine learning in Python

    • machine-learning
    • python
    • statistics
    • data-science
    • data-analysis
  5. Live search

    Find the people behind these repos

    Stars rank the projects. I can rank the engineers - maintainers, top contributors, and the people they work with. Fire one of these to see how it works.

    500 free credits on sign-up, no card needed.

  6. 5
    keras-team/keras64,321 · ⑂ 19,802

    Deep Learning for humans

    • deep-learning
    • tensorflow
    • neural-networks
    • machine-learning
    • data-science
    • python
  7. 6
    pandas-dev/pandas49,759 · ⑂ 20,404

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

    • data-analysis
    • pandas
    • flexible
    • alignment
    • python
    • data-science
  8. 7
    GokuMohandas/Made-With-ML49,548 · ⑂ 7,778

    Learn how to develop, deploy and iterate on production-grade ML applications.

    • machine-learning
    • deep-learning
    • pytorch
    • natural-language-processing
    • data-science
    • python
  9. 8

    Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.

    • interview-preparation
    • internships
    • jobs
    • university
    • fall-2026
    • github
  10. 9
    apache/airflow46,913 · ⑂ 17,873

    Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

    • airflow
    • apache
    • apache-airflow
    • python
    • scheduler
    • workflow
  11. 10
    streamlit/streamlit45,797 · ⑂ 4,385

    Streamlit — A faster way to build and share data apps.

    • python
    • machine-learning
    • data-science
    • deep-learning
    • data-visualization
    • streamlit
  12. Live search

    Who is hiring in this space?

    I read hiring signals across LinkedIn, GitHub, and the open web - so a topic list becomes a warm outreach list. Try one live.

    500 free credits on sign-up, no card needed.

  13. 11
    ray-project/ray43,875 · ⑂ 8,065

    Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

    • ray
    • distributed
    • parallel
    • machine-learning
    • reinforcement-learning
    • deep-learning
  14. 12
    gradio-app/gradio43,586 · ⑂ 3,607

    Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

    • machine-learning
    • models
    • ui
    • ui-components
    • interface
    • python
  15. 13

    10 Weeks, 20 Lessons, Data Science for All!

    • data-science
    • python
    • data-visualization
    • data-analysis
    • pandas
    • microsoft-for-beginners
  16. 14

    500 AI Machine learning Deep learning Computer vision NLP Projects with code

    • awesome
    • machine-learning
    • deep-learning
    • machine-learning-projects
    • deep-learning-project
    • computer-vision-project
  17. 15
    explosion/spaCy33,911 · ⑂ 4,723

    💫 Industrial-strength Natural Language Processing (NLP) in Python

    • natural-language-processing
    • data-science
    • machine-learning
    • python
    • cython
    • nlp
  18. 16
    eriklindernoren/ML-From-Scratch32,888 · ⑂ 5,490

    Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

    • machine-learning
    • deep-learning
    • deep-reinforcement-learning
    • machine-learning-from-scratch
    • data-science
    • data-mining
  19. Live search

    Turn any brief into a list like this

    I run natural-language searches across GitHub, LinkedIn, and the open web. Describe who you want and I'll build the shortlist.

    500 free credits on sign-up, no card needed.

  20. 17
    Lightning-AI/pytorch-lightning31,353 · ⑂ 3,797

    Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

    • python
    • deep-learning
    • artificial-intelligence
    • ai
    • pytorch
    • data-science
  21. 18
    AMAI-GmbH/AI-Expert-Roadmap31,238 · ⑂ 2,582

    Roadmap to becoming an Artificial Intelligence Expert in 2022

    • deep-learning
    • artificial-intelligence
    • roadmap
    • ai-roadmap
    • machine-learning
    • study-plan
  22. 19
    eugeneyan/applied-ml30,357 · ⑂ 3,996

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

    • applied-machine-learning
    • production
    • applied-data-science
    • machine-learning
    • data-science
    • reinforcement-learning

Find engineers shipping Data science

The list above ranks the most-starred public repositories tagged with the Data science topic, drawn from the public GitHub graph. Across 2,480 repositories tagged this way, the maintainers and top contributors are a tight cluster of the people actually building Data science.

Looking for engineers who’ve worked on Data science for real, not just listed it on LinkedIn? The fastest path is the contributor list of these repos. Their commits, issues, and READMEs are public proof of depth.

Refolk turns this list into a search. Ask for “maintainers of top Data science repos who are hiring”, Data science engineers in San Francisco”, or “founders shipping Data science” and Refolk returns a ranked shortlist with sources.

How this list is built

Refolk searched GitHub for public repositories tagged with the Data science topic, ranked them by stargazer count, and kept those with at least 50 stars. The list refreshes once a day.

Last refreshed: Sun, 20 Sep 2026 06:59:43 GMT

Search this list

Need a list like this for any search?

Refolk runs natural-language searches across GitHub, LinkedIn, and the open web. Try one of these:

500 free credits on sign-up, no card needed.

Browse other topics

See all repository lists.

Data science by language

Common questions

How are these repositories ranked?

By stars, with forks and recent activity as tiebreakers, read from the public GitHub API. The methodology section above has the details.

How fresh is the data?

The ranking re-renders at least daily. Last refreshed: Sun, 20 Sep 2026 06:59:43 GMT.

Can I find the maintainers and contributors behind these repos?

Yes. Stars rank the projects; I can rank the engineers - maintainers, top contributors, and the people they work with. You start with 500 free credits, no card required.

Can I use this list for hiring?

That's the point. I read hiring signals across GitHub, LinkedIn, and the open web, so a repo list turns into a shortlist of engineers worth talking to.

Try it on the search you came here for

Stop building boolean strings. Just describe the person.

Type one sentence. I plan the search, read GitHub, public LinkedIn and Crunchbase records, and the open web as it is right now, and hand back a ranked list with the reason next to every name.

  1. 01Describe them

    One plain sentence. Role, city, stack, stage, whatever matters to you.

  2. 02I read the web live

    GitHub, public LinkedIn and Crunchbase records, the open web. Not a database that went stale last quarter.

  3. 03You read the shortlist

    Ranked, with the reasoning under every name. Open a profile, ask a follow-up, narrow it down.

  • No boolean, no filters, no seat to buy. One box.
  • Read at search time, so a profile updated yesterday counts today.
  • Every step visible as it runs, every name with its reason.

500 free credits on sign-up. No card, no demo call. See real searches.

Keep exploring