Top 10 GitHub Repositories to Master AI, Machine Learning and Data Science

We know how difficult it is to find resources that can explain in details how everything works in machine learning (ML), data science, and AI. Today, in one place, we want to offer you a “collection of collections” of guides, lectures, books, projects, and papers that will help you master and fully understand these complex subjects, including algorithms, concepts, programming, and the math behind them.

Here are 10 GitHub Repositories with valuable resources on data science, ML and AI for any purpose:

1. 100 Days of ML Code (45.6k stars): Proposes a plan for studying Machine Learning aspects, such as Data PreProcessing, simple and multiple linear and logistic regression, SVM and KNN, decision trees, other math behind ML and much more.  → Explore more

2. Data Science For Beginners (28.4k stars): A Microsoft's 10-week, 20-lesson curriculum about Data Science. These lessons include videos, sketchnotes, quizzes, project guides, and assignments. → Explore more

3. Awesome Data Science (25.2k stars): Useful courses, tutorials, books, and media sources on Data Science, explaining what it is and its main algorithms. → Explore more

4. Data Science Masters (25.1k stars): Concerned with "upper-level" college course material in math, programming, economics, and related disciplines. → Explore more

5. Homemade Machine Learning (23.2k stars): Here you can practice implementing machine learning algorithms from scratch and understand math behind each algorithm. → Explore more

6. 500+ AI Projects List with Code (20.7k stars): Includes Deep Learning, Computer Vision, NLP, machine learning and AI projects with code. → Explore more

7. Awesome Artificial Intelligence (AI) (11k stars): Provides tools for text, image and video generation, and a wide range of useful courses, books, lectures, and papers.  → Explore more

8. Machine Learning Design Interview (9.9k stars): Provides a study guide to master Machine Learning interviews, including programming, ML fundamentals, system design and more. → Explore more

9. Data Science Interviews (9k stars): This one dives into data science theoretical and technical interview questions with detailed answers. → Explore more

10. Data Science Best Resources (2.9k stars): Offers a huge collection of data science resources, which cover software, platforms and techniques in one place. → Explore more

11. Our Twitter Library is always available to provide useful resources, such as lists of tools and models, papers and courses on various popular aspects of AI and machine learning for your convenience. :) → Explore more