21 Lessons, Get Started Building with Generative AI
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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- ml
- data-science
- machine-learning
- machine-learning-algorithms
Python Data Science Handbook: full text in Jupyter Notebooks
Learn how to develop, deploy and iterate on production-grade ML applications.
This is a repo with links to everything you'd ever want to learn about data engineering
Translated"开源大模型食用指南" (Open-Source Large Model Usage Guide): a tutorial tailor-made for Chinese users on quickly fine-tuning (full-parameter/LoRA) and deploying domestic and international open-source large language models (LLM) and multimodal large models (MLLM) in a Linux environment
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
- hacking
- penetration-testing
- hacking-series
- cybersecurity
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
- bayesian-methods
- pymc
- mathematical-analysis
- jupyter-notebook
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
- machine-learning
- trading
- investment
- finance
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
💿 Free software that works great, and also happens to be open-source Python.
Sample code and notebooks for Generative AI on Google Cloud, with Gemini platform
- generative-ai
- llm
- vertex-ai
- langchain
A collection of various deep learning architectures, models, and tips
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
- csharp
- java
- javascript
- mcp
Translated"Lee Hung-yi's Deep Learning Tutorial" (recommended by Professor Hung-yi Lee 👍, the Apple Book 🍎), PDF download address: https://github.com/datawhalechina/leedl-tutorial/releases
- machine-learning
- deep-learning
- leedl-tutorial
- cnn