nannyml: post-deployment data science in python

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

Code for the manim-generated scenes used in 3blue1brown videos

The de facto GitHub star history graph.

The book every data scientist needs on their desk.

Poisson Binomial Probability Distribution for Python

Lime: Explaining the predictions of any machine learning classifier

A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A game theoretic approach to explain the output of any machine learning model.

scikit-learn: machine learning in Python

A topic-centric list of HQ open datasets.

An open source platform for Python in the browser. https://pyscript.net Docs: https://docs.pyscript.net/ Try it: https://pyscript.com/ Community: https://discord.gg/HxvBtukrg2

An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification

A Rust🦀 implementation of CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning

An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification

Lecture notes for 'Interpretable Machine Learning' at WUT and UoW. Summer semester 2019/2020