1.patchy631 / ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
One has no future if one couldn't teach themself.
18 Lessons to Get Started Building AI Agents
TranslatedDive into LLMs: a series of hands-on programming tutorials
AirLLM 2.8T LLM inference with single 4GB GPU
21 Lessons, Get Started Building with Generative AI
Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
WeVisOne-VL is a powerful VLM by the WeChat Vision Team at Tencent, unifying object-level and pixel-level perception from points and boxes to masks and alpha mattes.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
This is a repo with links to everything you'd ever want to learn about data engineering
12 Weeks, 24 Lessons, AI for All!
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
TranslatedPython - 100 Days from Novice to Master
10 Weeks, 20 Lessons, Data Science for All!
Translated📚 Building large models from scratch
Anthropic's Interactive Prompt Engineering Tutorial
FinRL®: Financial Reinforcement Learning. 🔥
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Python Data Science Handbook: full text in Jupyter Notebooks
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Examples and guides for using the OpenAI API
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
Learn how to develop, deploy and iterate on production-grade ML applications.
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
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
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
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.
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
TranslatedAISystem mainly refers to AI systems, covering the full stack of underlying AI technologies, including AI chips, AI compilers, and AI inference and training frameworks
Translated✅ (Completed) Super comprehensive deep learning notes [Tudui PyTorch] [Li Mu Dive into Deep Learning] [Andrew Ng Deep Learning] [Dafei LLM Agent]
Google Research
Learn ML engineering for free in 4 months! Register here 👇🏼
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.
Python training for business analysts and traders
TranslatedThis project is a tutorial on developing large model applications, aimed at beginner developers. Read it online at: https://datawhalechina.github.io/llm-universe/
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Anthropic's educational courses
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
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
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
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.
Examples and guides for using the Gemini API
A High-Quality Real Time Upscaler for Anime Video
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.
Reference PyTorch implementation and models for DINOv3
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.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
A latent text-to-image diffusion model
A simple screen parsing tool towards pure vision based GUI agent
TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")
TranslatedAn introductory LLM tutorial for developers, the Chinese version of Andrew Ng's large model course series
Sample code and notebooks for Generative AI on Google Cloud, with Gemini platform
TranslatedChinese tutorial on reinforcement learning (Mushroom Book 🍄), read online at: https://datawhalechina.github.io/easy-rl/
Practice your pandas skills!
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
The fastai book, published as Jupyter Notebooks
This repository contains implementations and illustrative code to accompany DeepMind publications
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Performance analysis of predictive (alpha) stock factors
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
The fastai deep learning library
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.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
TranslatedLLM teaching material for high school students: based on Karpathy's microgpt, for Google Colab
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.
PyTorch code and models for the DINOv2 self-supervised learning method.
MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases
Companion webpage to the book "Mathematics For Machine Learning"
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Course Files for Complete Python 3 Bootcamp Course on Udemy
A game theoretic approach to explain the output of any machine learning model.
Learn OpenCV : C++ and Python Examples
YSDA course in Natural Language Processing
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Automatic extraction of relevant features from time series:
Instructional notebooks on music information retrieval.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
A course in reinforcement learning in the wild
Quantitative analysis, strategies and backtests
The repository host gives no description.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
A collection of various deep learning architectures, models, and tips
Kubernetes Community Documentation
Foundational Models for State-of-the-Art Speech and Text Translation
TranslatedThe pytorch handbook is an open-source book that aims to help friends who want to use PyTorch for deep learning development and research get started quickly. All of the PyTorch tutorials it contains have been tested to ensure they run successfully.
QLoRA: Efficient Finetuning of Quantized LLMs