- San Francisco, CA
- http://stephanhoyer.com
- @shoyer
Stars
scikit-learn: machine learning in Python
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The fundamental package for scientific computing with Python.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
NumPy aware dynamic Python compiler using LLVM
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
🐚 Python-powered shell. Full-featured, cross-platform and AI-friendly.
A debugging and profiling tool that can trace and visualize python code execution
Efficiently computes derivatives of NumPy code.
A system-level, binary package and environment manager running on all major operating systems and platforms.
(OLD REPO) Line-by-line profiling for Python - Current repo ->
Quickly and accurately render even the largest data.
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
An implementation of chunked, compressed, N-dimensional arrays for Python.
A differentiable PDE solving framework for machine learning