1.patchy631 / ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
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84 repositories by Attention Score · Oct 28, 2026 – Nov 3, 2026 (UTC)
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
21 Lessons, Get Started Building with Generative AI
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
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]
Learn ML engineering for free in 4 months! Register here 👇🏼
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/
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Anthropic's educational courses
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
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
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
高校生向けLLM教材: Karpathy microgptベース,Google Colab用
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.
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
Learn OpenCV : C++ and Python Examples
YSDA course in Natural Language Processing
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
🤖 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
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.
Tutorials and programming exercises for learning Q# and quantum computing
TranslatedDeep Learning Tutorial, excellent articles
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
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 ;)
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》)
Lists of company wise questions available on leetcode premium. Every csv file in the companies directory corresponds to a list of questions on leetcode for a specific company based on the leetcode company tags. Updated as of May, 2022.
Simple tutorials using Google's TensorFlow Framework
TranslatedCode implementation of 《统计学习方法》 (Statistical Learning Methods)
TranslatedThis project covers the knowledge points and code implementations frequently asked about in Machine Learning, Deep Learning, and NLP interviews, and it is also the basic theoretical knowledge that an algorithm engineer must master.
This repository contains demos I made with the Transformers library by HuggingFace.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
12 Weeks, 24 Lessons, IoT for All!
The "Python Machine Learning (1st edition)" book code repository and info resource
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Algorithms for outlier, adversarial and drift detection
A collection of Jupyter notebooks showing how to use the Qiskit SDK
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
llama3 implementation one matrix multiplication at a time
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis
open source E-book on statistical physics
Quantum Classification tutorial using Microsoft Quantum Development Kit