ml-retreat

ml-retreat

Machine Learning Journal for Intermediate to Advanced Topics.

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ML-Retreat is a comprehensive machine learning library designed to simplify and streamline the process of building and deploying machine learning models. It provides a wide range of tools and utilities for data preprocessing, model training, evaluation, and deployment. With ML-Retreat, users can easily experiment with different algorithms, hyperparameters, and feature engineering techniques to optimize their models. The library is built with a focus on scalability, performance, and ease of use, making it suitable for both beginners and experienced machine learning practitioners.

README:

ML Retreat: Advanced ML Learning Journal

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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 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:

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