Examples and guides for using the OpenAI API
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A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
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
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
- python
- python-3
- programming
- practice
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
- deep-learning
- deep-learning-tutorial
- pytorch
- pytorch-tutorial
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
Examples and guides for using the Gemini API
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
:satellite: Simple and ready-to-use tutorials for TensorFlow
- tensorflow
- python
- deep-learning
- deep-learning-tutorial
Your new Mentor for Data Science E-Learning.
- tensorflow
- machine-learning
- machine-vision
- datascience
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Python training for business analysts and traders
- python
- jupyter
- jupyterlab
- binder
Solve puzzles. Learn CUDA.
- cuda
- machine-learning
- puzzles
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Simple tutorials using Google's TensorFlow Framework
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
- tensorflow
- machine-learning
- regression
- convolutional-neural-networks
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
- machine-learning
- deep-learning
- lstm
- human-activity-recognition
[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..
- templates
- opensource
- naas
- notebooks-templates