Resources

This is a collection of resources that I find useful in my journey as a data scientist and machine learning engineer. I will keep updating this list as I come across new resources. I may try to organize them into categories in the future.

  1. Using LLM in GitHub Actions

  2. The Missing Semester

  3. MLOps Zoomcamp

  4. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

  5. System Design Primer

  6. LLMs from Scratch

  7. Github Actions with Conda

  8. DevOps for Data Scientists

  9. Machine Learning Interviews

  10. Scientific Visualization

  11. Good Documentation, Better Productivity

  12. RFCs and Design Docs

  13. The Pragmatic Engineer

  14. Technical Documentation in Software Development: Types, Best Practices, and Tools

  15. Eric J. Ma

  16. Software Design by Example

  17. Code Kata

  18. PyCoders Weekly

  19. PyVideo

  20. Real Python

  21. PyBites

  22. Ploeh Blog

  23. Danluu posts

  24. Martin Fowler

  25. Luciano Ramalho - Fluent Python

  26. Netflix Tech Blog

  27. LinkedIn Engineering Blog

  28. Uber Engineering Blog

  29. Airbnb Engineering Blog

  30. Pinterest Engineering Blog

  31. Dropbox Tech Blog

  32. YouTube Video Ollama