Highlights
- Pro
Lists (1)
Stars
📚 Freely available programming books
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Models and examples built with TensorFlow
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Query Engine for AI Analytics: Build self-reasoning agents across all your live data
Official inference framework for 1-bit LLMs
A book-in-progress about the Linux kernel and its insides.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Typer, build great CLIs. Easy to code. Based on Python type hints.
Asynchronous HTTP client/server framework for asyncio and Python
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
An educational resource to help anyone learn deep reinforcement learning.
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
A PyTorch implementation of EfficientNet
A system for quickly generating training data with weak supervision
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
Example code for the book Fluent Python, 1st Edition (O'Reilly, 2015)
Official git repository for Biopython (originally converted from CVS)
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
LightGlue: Local Feature Matching at Light Speed (ICCV 2023)
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
A highly efficient implementation of Gaussian Processes in PyTorch