Flint: A Time Series Library for Apache Spark The ability to analyze time series data at scale is critical for the success of finance and IoT applicat

Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui

Robotics Toolbox for Python A Python implementation of the Robotics Toolbox for MATLAB® GitHub repository Documentation Wiki (examples and details) Sy

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn

TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models

fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa

Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

formulae formulae is a Python library that implements Wilkinson's formulas for mixed-effects models. The main difference with other implementations li

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

napari-sklearn-decomposition A simple plugin to use with napari This napari plug

MBTR is a python package for multivariate boosted tree regressors trained in parameter space.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

MaD GUI Machine Learning and Data Analytics Graphical User Interface MaD GUI is a basis for graphical annotation and computational analysis of time se

AutoML Service Deploy automated machine learning (AutoML) as a service using Flask, for both pipeline training and pipeline serving. The framework imp