21 Lessons, Get Started Building with Generative AI
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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
- gpt
- large-language-models
- llm
- python
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- ml
- data-science
- machine-learning
- machine-learning-algorithms
18 Lessons to Get Started Building AI Agents
- agentic-ai
- agentic-framework
- agentic-rag
- ai-agents
A latent text-to-image diffusion model
12 Weeks, 24 Lessons, AI for All!
Python Data Science Handbook: full text in Jupyter Notebooks
- scikit-learn
- numpy
- python
- jupyter-notebook
Learn how to develop, deploy and iterate on production-grade ML applications.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
AirLLM 2.8T LLM inference with single 4GB GPU
- chinese-nlp
- finetune
- generative-ai
- instruct-gpt
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
Google Research
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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
The fastai deep learning library
- deep-learning
- machine-learning
- pytorch
- python
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
A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
The fastai book, published as Jupyter Notebooks
- notebooks
- fastai
- deep-learning
- machine-learning
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained