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Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Public facing notes page
A collection of (mostly) technical things every software developer should know about
Detailed python notes & code for lectures and exercises of Andrej Karpathy's course "Neural Networks: Zero to Hero." The course is focused on building neural networks from scratch.
Jupyter notebooks accompanying Andrej Karpathy's neural network lectures. Includes extended notes and direct Colab links.
Neural Networks: Zero to Hero
200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.
https://huyenchip.com/ml-interviews-book/
Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.
Implement a reasoning LLM in PyTorch from scratch, step by step
Learn ML engineering for free in 4 months! Register here 👇🏼
ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP
Machine Learning Engineering Open Book
Lab assignments for Introduction to Data-Centric AI, MIT IAP 2024 👩🏽💻
VIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models
VIP cheatsheets for Stanford's CS 230 Deep Learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
A launch point for your personal nvim configuration
A library for mechanistic interpretability of GPT-style language models
TinyGPUs, making graphics hardware for 1990s games
You like pytorch? You like micrograd? You love tinygrad! ❤️
my repo for the the MLops ZoomCamp course from DataTalksClub https://github.com/DataTalksClub/mlops-zoomcamp
Chat with your own data - LLM+RAG workshop
AI Dev Tools Zoomcamp is a free course that helps you use AI tools to write better code, faster. We're starting the first cohort of this course on November 18, 2025! Sign up here to join us 👇🏼
European Summer of Code 2025 - Information and Projects
Workbooks for coding projects from Andrej Karpathy's Zero-to-Hero series. Step-by-step guides, exercises, and solutions with direct Colab links.