awesome-machine-learning

A machine learning / bayesian inference assigning attributes to objects.

An Open Source Distributed Framework for Reinforcement Learning that makes build and train your agents easily.

А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.

Code for Data Science at Olin College, Spring 2014.

Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.

Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.

Open source C# framework for developers and researchers in the fields of Computer Vision and Artificial Intelligence. Development has now shifted to GitHub.

A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.

Abstract Algebra for Scala.

CPU and GPU-accelerated Machine Learning Library.

CPU and GPU-accelerated matrix library intended to support large-scale exploratory data analysis.

Bioinformatics for the Scala programming language

Breeze is a numerical processing library for Scala.

A machine learning library by Airbnb designed from the ground up to be human friendly.

A Java Toolbox for Scalable Probabilistic Machine Learning.

Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open-source natural language processing system for information extraction from electronic medical record clinical free-text.

A Java library for genetic algorithms, evolutionary computation, and stochastic local search, with a focus on self-adaptation / self-tuning, as well as parallel execution.

ClearTK provides a framework for developing statistical natural language processing (NLP) components in Java and is built on top of Apache UIMA.

Open Source Toolkit For Speech Recognition purely based on Java speech recognition library.

ahaz: Regularization for semiparametric additive hazards regression.

arules: Mining Association Rules and Frequent Itemsets

biglasso: Extending Lasso Model Fitting to Big Data in R.

bmrm: Bundle Methods for Regularized Risk Minimization Package.

Boruta: A wrapper algorithm for all-relevant feature selection.

bst: Gradient Boosting.

A toolbox framework of AI modules written in Swift: Graphs/Trees, Linear Regression, Support Vector Machines, Neural Networks, PCA, KMeans, Genetic Algorithms, MDP, Mixture of Gaussians.

A curated list of pretrained CoreML models.

A curated list of machine learning models in CoreML format.

Fast Neural Networks framework built on top of Metal. Supports TensorFlow models.

The iOS and OS X neural network framework.