Machine Learning Journal for Intermediate to Advanced Topics.
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README
ML Retreat: Advanced ML Learning Journal
Current Grind: Mechanistic Interpretability
This repository is my personal journal of learning advanced topics in machine learning. It includes an in-depth understanding of fundamentals + additional must-read/watch recourses for more nuanced subjects.
📝 My Notes
Build an LLM from Scratch |
LLM Hallucination |
LLM Edge: Beyond Attention |
Introduction to GNNs |
AlphaFold3: a machine learning look |
Natural Language Processing |
📕 Table of Content
If you go to th Days Folder you can find a list of all the topics I have covered. However, for easier access to a specific subject, check out this table to find which days to go through.
| Subject | Check out: |
|---|---|
| Large Language Models | from Day 003 to Day 016 |
| Graph Neural Networks | from Day 017 to Day 022 |
| AlphaFold 3 | Day 23 |
🎯 Goals
My goals of this learning retreat includes studying:
- Ilya Sutskever's top 30 must-read research papers
- Most of Distilled AI's Blogs
- Artem Kirsanov's AI/ML Playlist
- Andrej Karpathy's golden Neural Net Playlist
- In-depth understanding/implementations of Transformers
- LLMs and related topics ✅
- LLM Halucination in depth ✅
- Quantum Machine Learning
- Jax
- Energy-Based Models