Lists (3)
Stars
Apache DataFusion Ballista Distributed Query Engine
pratrical crash course on pytorch by reproducing some published biology-related deep-learning models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Python code for "Probabilistic Machine learning" book by Kevin Murphy
A Visual Exploration of Gaussian Processes
Interactive Markov-chain Monte Carlo Javascript demos
Tutorials and sampling algorithm comparisons
Interactive visualization of Gaussian processes
"Deep Generative Modeling": Introductory Examples
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Pen and paper exercises in machine learning
Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc.
Optax is a gradient processing and optimization library for JAX.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
A small package to create visualizations of PyTorch execution graphs
Tutorials on creating a reproducible and maintainable data science project
JAX - A curated list of resources https://github.com/google/jax
Flax is a neural network library for JAX that is designed for flexibility.
An inflation calculator application for various countries.
Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
Companion webpage to the book "Mathematics For Machine Learning"
Apps (mostly streamlit) for the "Probabilistic Machine Learning" Lecture course at the University of Tübingen
Streamlit — A faster way to build and share data apps.