# ML Retreat: Advanced ML Learning Journal ![header](assets/header.png) **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.
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## 📝 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](Days/) 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](https://aman.ai/primers/ai/top-30-papers/) - [Most of Distilled AI's Blogs](https://aman.ai/primers/ai/) - [Artem Kirsanov's AI/ML Playlist](https://www.youtube.com/playlist?list=PLgtmMKe4spCPsxyMpg-sxf3EcbsFYlzPK) - [Andrej Karpathy's golden Neural Net Playlist](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) - In-depth understanding/implementations of Transformers - LLMs and related topics ✅ - LLM Halucination in depth ✅ - Quantum Machine Learning - Jax - Energy-Based Models