Stars
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Examples and guides for using the OpenAI API
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.
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
A collection of various deep learning architectures, models, and tips
Foundational Models for State-of-the-Art Speech and Text Translation
This repository contains demos I made with the Transformers library by HuggingFace.
LAVIS - A One-stop Library for Language-Vision Intelligence
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
An open-source, low-code machine learning library in Python
Image restoration with neural networks but without learning.
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…
The fastest way to create an HTML app
COCO API - Dataset @ http://cocodataset.org/
A scikit-learn compatible neural network library that wraps PyTorch
Reference models and tools for Cloud TPUs.
The 3rd edition of course.fast.ai
A small package to create visualizations of PyTorch execution graphs
Bayesian optimization in PyTorch