Python logging made (stupidly) simple

🔬 Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.

Interactive Gaussian Processes

Deep Gaussian Processes with Importance-Weighted Variational Inference

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Gaussian processes in TensorFlow

Pretty, minimal and fast ZSH prompt

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

An extension to Sacred for automated hyperparameter optimization.

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Bayesian Modeling and Probabilistic Programming in Python

Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

Deep Learning for humans

JupyterLab computational environment.

The uncompromising Python code formatter

Automated Machine Learning with scikit-learn

Efficiently computes derivatives of NumPy code.

Notebooks about Bayesian methods for machine learning

Kriging Toolkit for Python

Quilt is a data mesh for connecting people with actionable data

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Bayesian Reinforcement Learning in Tensorflow

(Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.

An Open Source Machine Learning Framework for Everyone

Bayesian Optimization using GPflow

ELFI - Engine for Likelihood-Free Inference

A highly efficient implementation of Gaussian Processes in PyTorch

Probabilistic Torch is library for deep generative models that extends PyTorch

🦉 Data Versioning and ML Experiments