21 Lessons, Get Started Building with Generative AI
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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
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.
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.
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
This is a repo with links to everything you'd ever want to learn about data engineering
10 Weeks, 20 Lessons, Data Science for All!
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
Course Files for Complete Python 3 Bootcamp Course on Udemy
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
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.
TranslatedAn introductory LLM tutorial for developers, the Chinese version of Andrew Ng's large model course series
- cookbook
- llm
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.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.