21 Lessons, Get Started Building with Generative AI
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18 Lessons to Get Started Building AI Agents
- agentic-ai
- agentic-framework
- agentic-rag
- ai-agents
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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
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
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
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
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
- pytorch
- pytorch-tutorials
- pytorch-tutorials-cn
- deep-learning
Understanding Deep Learning - Simon J.D. Prince
TranslatedTensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0 version introductory example code and hands-on tutorials.
- tensorflow
- tensorflow-examples
- tensorflow-tutorials
- tensorflow-2
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
Mostly experiments based on "Advances in financial machine learning" book
💸 Papers and Code Implements for Quantitative-Trading
A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.
An Icon classifier made with TFLite Model Maker and deployed to Android with ML Model Binding.
- tensorflow-lite
- tflite
- computer-vision
- deep-learning