This repository aims to provide a comprehensive collection of resources and tools for anyone interested in machine learning. It serves as a learning platform as well as a reference point for advanced topics in the field.
git clone https://github.com/martintmv-git/ml-playground.git
cd ml-playground- Neural Networks and Deep Learning by Michael Nielsen
- Machine Learning Yearning by Andrew Ng (Available for free as a downloadable PDF)
- Bayesian Methods for Hackers by Cameron Davidson-Pilon
- Pattern Recognition and Machine Learning by Christopher M. Bishop
- ISL with Python
- No bullshit guide to linear algebra by Ivan Savov
- No bullshit guide to math and physics by Ivan Savov
- Data Science from Scratch: First Principles with Python, Edition: 2 by Joel Grus
- The Hundred-Page Machine Learning Book by Andriy Burkov
- Machine Learning Engineering by Andriy Burkov
- The Little Book of Deep Learning
- Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- Machine Learning with PyTorch and Scikit-Learn by Sebastian Raschka
- Attention is All You Need
- 3Blue1Brown - Essence of linear algebra
- 3Blue1Brown - Neural networks
- Mathematics for Machine Learning - Coursera
- Machine Learning Specialization - Coursera
- IBM AI Engineer Professional Certificate - Coursera
- Algebra 1M
- Differential and Integral Calculus
- PyTorch for Deep Learning
- LLM Course Repository
- Andrej Karpathy - Intro to Large Language Models
- Zero to GPT - A Guide
- Andrej Karpathy - Let's build GPT: from scratch, in code, spelled out
- Andrej Karpathy - Let's build the GPT Tokenizer
- Andrej Karpathy - The spelled-out intro to neural networks and backpropagation: building micrograd
- NLP Workshop - Olaf Janssen
- Radu Mariescu-Istodor - Machine Learning Course in JavaScript
- Hugging Face Transformers
- OpenAI Cookbook
- Keras
- scikit-learn
- PyTorch
- TensorFlow
- Jupyter Notebooks
- Google Colab
- Papers with Code
- Weights & Biases
- MLflow
Contributions are welcome! Just open a pull request and we'll review it together.
