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An opinionated list of awesome Python frameworks, libraries, software and resources.
Models and examples built with TensorFlow
openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 275+ supported cars.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
⚡ A Fast, Extensible Progress Bar for Python and CLI
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.
Graph Neural Network Library for PyTorch
Convert Machine Learning Code Between Frameworks
Bayesian Modeling and Probabilistic Programming in Python
Deep universal probabilistic programming with Python and PyTorch
An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Automated Machine Learning with scikit-learn
Implementation of Graph Convolutional Networks in TensorFlow
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
Cookiecutter template for a Python package.
A highly efficient implementation of Gaussian Processes in PyTorch
Official project repository for the Setuptools build system
Learning in infinite dimension with neural operators.
napari: a fast, interactive, multi-dimensional image viewer for python
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Flexible Python configuration system. The last one you will ever need.
Comprehensive collection of programming styles using a simple computational task, term frequency
Exploratory analysis of Bayesian models with Python
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
