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Data science
Deep Learning
Deep learning courses
Diagramming tools
Diff tools
Federated learning
Font tools
Fonts
Game engines
GANs
Geometric ML
Graph ML
Machine Learning 🤖 🎓
Machine learning courses
Markdown editors
Math
ML config
ML/DL datasets
ML: Jax
ML: RL
Music
NLP
Notes manager
Personal projects
🐍 Python type checkers
Raytracing, rendering, etc.
💼 Work-related projects
Stars
🦜🔗 Build context-aware reasoning applications
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
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.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Python Data Science Handbook: full text in Jupyter Notebooks
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Learn how to design, develop, deploy and iterate on production-grade ML applications.
🔊 Text-Prompted Generative Audio Model
12 Weeks, 24 Lessons, AI for All!
10 Weeks, 20 Lessons, Data Science for All!
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.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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 ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
A game theoretic approach to explain the output of any machine learning model.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
The fastai book, published as Jupyter Notebooks
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…
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
A guidance language for controlling large language models.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Instruct-tune LLaMA on consumer hardware
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 filte…
A collection of various deep learning architectures, models, and tips