Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
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The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Translated📚 Building large models from scratch
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.
TranslatedAn introductory LLM tutorial for developers, the Chinese version of Andrew Ng's large model course series
- cookbook
- llm
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
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
- machine-learning
- trading
- investment
- finance
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
- funds
- machine-learning
- pytrade
- quantitative-finance
Sample code and notebooks for Generative AI on Google Cloud, with Gemini platform
- generative-ai
- llm
- vertex-ai
- langchain
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
- open-vocabulary-detection
- open-vocabulary-segmentation
- data-generation
- automatic-labeling-system
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
FinRL®: Financial Reinforcement Learning. 🔥
- deep-reinforcement-learning
- drl-trading-agents
- stock-trading
- drl-algorithms
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