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Learning function operators with neural networks.
More routines for operating on iterables, beyond itertools
Collection of design patterns that came to me in feverish nights - so bad they are good!
Software design principles for machine learning applications
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
a simple script for splitting the git history of a file
Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
A high-performance implementation of Wilkinson formulas for Python.
Hackable and optimized Transformers building blocks, supporting a composable construction.
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
An unnecessarily tiny implementation of GPT-2 in NumPy.
The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
Create beautiful, publication-quality books and documents from computational content.
Parse and execute ipynb files in Sphinx
PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., C…
Open source book dedicated to helping you to make the best possible sourdough bread at home.
Differentiable convex optimization layers
The fundamental package for scientific computing with Python.
A derivative-free solver for general nonlinear optimization.
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
The entrance repository of Markdown presentation ecosystem
A minimal cookiecutter template for a project with pytask.