u/Limp-Government-710

(2nd Year Tier-3 student btw)

I’m currently learning DSA seriously and I’ll probably finish my topics in around 15–20 days. After that I’m planning to start deeper AI/ML learning and build projects consistently.

Before I start dumping random notebooks on GitHub, I wanted advice from people already in the field:

What kind of repositories/projects actually make a beginner GitHub profile look strong?

Should I focus more on:

- end-to-end projects,

- clean EDA notebooks,

- deployment,

- research paper implementations,

- Kaggle,

- open source,

- or documenting my learning journey?

Also, what are some mistakes that instantly make an ML GitHub look low effort or tutorial-copied?

Would appreciate honest advice and examples.