Deep Learning for humans

scikit-learn: machine learning in Python

The fundamental package for scientific computing with Python.

A generative world for general-purpose robotics & embodied AI learning.

A hyperparameter optimization framework

Bayesian Modeling and Probabilistic Programming in Python

A python library for user-friendly forecasting and anomaly detection on time series.

A unified framework for machine learning with time series

A tool that bootstraps your dotfiles ⚡️

Probabilistic time series modeling in Python

NeuralProphet: A simple forecasting package

The machine learning toolkit for time series analysis in Python

An intuitive library to add plotting functionality to scikit-learn objects.

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

Exploratory analysis of Bayesian models with Python

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

Automated Time Series Forecasting

An intuitive library to extract features from time series.

DJI Tello drone controller python package

An extension of XGBoost to probabilistic modelling

Python module for machine learning time series:

Flexible time series feature extraction & processing

Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/

An extension of LightGBM to probabilistic modelling

Metrics for verifying forecasts

Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.

Probabilistic Gradient Boosting Machines

Python package for missing-data imputation with deep learning

Sliders to control matplotlib and other interactive goodies. Works in any interactive backend and even uses ipywidgets when in a Jupyter notebook