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Awesome

An open API service indexing awesome lists of open source software.

awesome-machine-learning

Machine Learning
https://github.com/jacob98415/awesome-machine-learning

Last synced: 9 days ago
JSON representation

  • Java

    • [Tools](#tools-1)

      • AMIDST Toolbox - A Java Toolbox for Scalable Probabilistic Machine Learning.
      • ELKI - Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)
      • RankLib - RankLib is a library of learning to rank algorithms. **[Deprecated]**
      • Stanford Classifier - A classifier is a machine learning tool that will take data items and place them into one of k classes.
      • Storm - Storm is a distributed realtime computation system.
      • Keras Beginner Tutorial - Friendly guide on using Keras to implement a simple Neural Network in Python.
      • LingPipe - A tool kit for processing text using computational linguistics.
      • ClearTK - ClearTK provides a framework for developing statistical natural language processing (NLP) components in Java and is built on top of Apache UIMA. **[Deprecated]**
      • NLP4J - The NLP4J project provides software and resources for natural language processing. The project started at the Center for Computational Language and EducAtion Research, and is currently developed by the Center for Language and Information Research at Emory University. **[Deprecated]**
      • CogcompNLP - This project collects a number of core libraries for Natural Language Processing (NLP) developed in the University of Illinois' Cognitive Computation Group, for example `illinois-core-utilities` which provides a set of NLP-friendly data structures and a number of NLP-related utilities that support writing NLP applications, running experiments, etc, `illinois-edison` a library for feature extraction from illinois-core-utilities data structures and many other packages.
      • aerosolve - A machine learning library by Airbnb designed from the ground up to be human friendly.
      • AMIDST Toolbox - A Java Toolbox for Scalable Probabilistic Machine Learning.
      • Chips-n-Salsa - 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.
      • Datumbox - Machine Learning framework for rapid development of Machine Learning and Statistical applications.
      • H2O - ML engine that supports distributed learning on Hadoop, Spark or your laptop via APIs in R, Python, Scala, REST/JSON.
      • htm.java - General Machine Learning library using Numenta’s Cortical Learning Algorithm.
      • liblinear-java - Java version of liblinear.
      • Mahout - Distributed machine learning.
      • Hydrosphere Mist - a service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.
      • ORYX - Lambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.
      • rapaio - statistics, data mining and machine learning toolbox in Java.
      • LBJava - Learning Based Java is a modelling language for the rapid development of software systems, offers a convenient, declarative syntax for classifier and constraint definition directly in terms of the objects in the programmer's application.
      • knn-java-library - Just a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.
      • Hadoop - Hadoop/HDFS.
      • Onyx - Distributed, masterless, high performance, fault tolerant data processing. Written entirely in Clojure.
      • Spark - Spark is a fast and general engine for large-scale data processing.
      • Impala - Real-time Query for Hadoop.
      • Deeplearning4j - Scalable deep learning for industry with parallel GPUs.
      • deepjavalibrary/djl - Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning, designed to be easy to get started with and simple to use for Java developers.
      • Meka - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
      • Neuroph - Neuroph is lightweight Java neural network framework.
      • SystemML - flexible, scalable machine learning (ML) language.
      • RapidMiner - RapidMiner integration into Java code.
      • DataMelt - Mathematics software for numeric computation, statistics, symbolic calculations, data analysis and data visualization.

  • JavaScript

    • [Tools](#tools-1)

      • Twitter-text - A JavaScript implementation of Twitter's text processing library.
      • D3.js
      • High Charts
      • chartjs
      • dimple
      • amCharts
      • C3.js - customizable library based on D3.js for easy chart drawing.
      • Datamaps - Customizable SVG map/geo visualizations using D3.js. **[Deprecated]**
      • ZingChart - library written on Vanilla JS for big data visualization.
      • cheminfo - Platform for data visualization and analysis, using the [visualizer](https://github.com/npellet/visualizer) project.
      • Learn JS Data
      • AnyChart
      • FusionCharts
      • Convnet.js - ConvNetJS is a JavaScript library for training Deep Learning models[DEEP LEARNING] **[Deprecated]**
      • figue - K-means, fuzzy c-means and agglomerative clustering.
      • mil-tokyo - List of several machine learning libraries.
      • Heroes Wear Masks - A fun TensorFlow.js-based oracle that tells, whether one wears a face mask or not. It can even tell when one wears the mask incorrectly.
      • Rock Paper Scissors - Rock Paper Scissors trained in the browser with TensorFlow.js
      • natural - General natural language facilities for node.
      • Knwl.js - A Natural Language Processor in JS.
      • Retext - Extensible system for analyzing and manipulating natural language.
      • NLP Compromise - Natural Language processing in the browser.
      • nlp.js - An NLP library built in node over Natural, with entity extraction, sentiment analysis, automatic language identify, and so more.
      • dc.js
      • dimple
      • D3xter - Straight forward plotting built on D3. **[Deprecated]**
      • statkit - Statistics kit for JavaScript. **[Deprecated]**
      • datakit - A lightweight framework for data analysis in JavaScript
      • Z3d - Easily make interactive 3d plots built on Three.js **[Deprecated]**
      • Learn JS Data
      • Auto ML - Automated machine learning, data formatting, ensembling, and hyperparameter optimization for competitions and exploration- just give it a .csv file! **[Deprecated]**
      • Clusterfck - Agglomerative hierarchical clustering implemented in JavaScript for Node.js and the browser. **[Deprecated]**
      • Clustering.js - Clustering algorithms implemented in JavaScript for Node.js and the browser. **[Deprecated]**
      • Gaussian Mixture Model - Unsupervised machine learning with multivariate Gaussian mixture model.
      • Node-fann - FANN (Fast Artificial Neural Network Library) bindings for Node.js **[Deprecated]**
      • Keras.js - Run Keras models in the browser, with GPU support provided by WebGL 2.
      • Kmeans.js - Simple JavaScript implementation of the k-means algorithm, for node.js and the browser. **[Deprecated]**
      • LDA.js - LDA topic modelling for Node.js
      • Learning.js - JavaScript implementation of logistic regression/c4.5 decision tree **[Deprecated]**
      • machinelearn.js - Machine Learning library for the web, Node.js and developers
      • Node-SVM - Support Vector Machine for Node.js
      • Brain - Neural networks in JavaScript **[Deprecated]**
      • Brain.js - Neural networks in JavaScript - continued community fork of [Brain](https://github.com/harthur/brain).
      • Bayesian-Bandit - Bayesian bandit implementation for Node and the browser. **[Deprecated]**
      • Synaptic - Architecture-free neural network library for Node.js and the browser.
      • kNear - JavaScript implementation of the k nearest neighbors algorithm for supervised learning.
      • NeuralN - C++ Neural Network library for Node.js. It has advantage on large dataset and multi-threaded training. **[Deprecated]**
      • kalman - Kalman filter for JavaScript. **[Deprecated]**
      • shaman - Node.js library with support for both simple and multiple linear regression. **[Deprecated]**
      • ml.js - Machine learning and numerical analysis tools for Node.js and the Browser!
      • ml5 - Friendly machine learning for the web!
      • Pavlov.js - Reinforcement learning using Markov Decision Processes.
      • JSMLT - Machine learning toolkit with classification and clustering for Node.js; supports visualization (see [visualml.io](https://visualml.io)).
      • xgboost-node - Run XGBoost model and make predictions in Node.js.
      • Netron - Visualizer for machine learning models.
      • tensor-js - A deep learning library for the browser, accelerated by WebGL and WebAssembly.
      • WebDNN - Fast Deep Neural Network JavaScript Framework. WebDNN uses next generation JavaScript API, WebGPU for GPU execution, and WebAssembly for CPU execution.
      • stdlib - A standard library for JavaScript and Node.js, with an emphasis on numeric computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
      • sylvester - Vector and Matrix math for JavaScript. **[Deprecated]**
      • simple-statistics - A JavaScript implementation of descriptive, regression, and inference statistics. Implemented in literate JavaScript with no dependencies, designed to work in all modern browsers (including IE) as well as in Node.js.
      • regression-js - A javascript library containing a collection of least squares fitting methods for finding a trend in a set of data.
      • Lyric - Linear Regression library. **[Deprecated]**
      • GreatCircle - Library for calculating great circle distance.
      • MLPleaseHelp - MLPleaseHelp is a simple ML resource search engine. You can use this search engine right now at [https://jgreenemi.github.io/MLPleaseHelp/](https://jgreenemi.github.io/MLPleaseHelp/), provided via GitHub Pages.
      • Pipcook - A JavaScript application framework for machine learning and its engineering.
      • The Bot - Example of how the neural network learns to predict the angle between two points created with [Synaptic](https://github.com/cazala/synaptic).
      • Half Beer - Beer glass classifier created with [Synaptic](https://github.com/cazala/synaptic).
      • TensorFlow.js - A WebGL accelerated, browser based JavaScript library for training and deploying ML models.
      • Decision Trees - NodeJS Implementation of Decision Tree using ID3 Algorithm. **[Deprecated]**
      • science.js - Scientific and statistical computing in JavaScript. **[Deprecated]**
      • DN2A - Digital Neural Networks Architecture. **[Deprecated]**
      • NVD3.js
      • Nivo - built on top of the awesome d3 and Reactjs libraries

  • Julia

    • [Tools](#tools-1)

      • Flux - Relax! Flux is the ML library that doesn't make you tensor
      • MachineLearning - Julia Machine Learning library. **[Deprecated]**
      • MLBase - A set of functions to support the development of machine learning algorithms.
      • PGM - A Julia framework for probabilistic graphical models.
      • DA - Julia package for Regularized Discriminant Analysis.
      • Regression - Algorithms for regression analysis (e.g. linear regression and logistic regression). **[Deprecated]**
      • Local Regression - Local regression, so smooooth!
      • Naive Bayes - Simple Naive Bayes implementation in Julia. **[Deprecated]**
      • Simple MCMC - basic MCMC sampler implemented in Julia. **[Deprecated]**
      • Distances - Julia module for Distance evaluation.
      • Decision Tree - Decision Tree Classifier and Regressor.
      • Neural - A neural network in Julia.
      • MCMC - MCMC tools for Julia. **[Deprecated]**
      • Mamba - Markov chain Monte Carlo (MCMC) for Bayesian analysis in Julia.
      • GLM - Generalized linear models in Julia.
      • Gaussian Processes - Julia package for Gaussian processes.
      • Online Learning
      • Clustering - Basic functions for clustering data: k-means, dp-means, etc.
      • SVM - SVM for Julia. **[Deprecated]**
      • Kernel Density - Kernel density estimators for Julia.
      • MultivariateStats - Methods for dimensionality reduction.
      • NMF - A Julia package for non-negative matrix factorization.
      • ANN - Julia artificial neural networks. **[Deprecated]**
      • Mocha - Deep Learning framework for Julia inspired by Caffe. **[Deprecated]**
      • XGBoost - eXtreme Gradient Boosting Package in Julia.
      • ManifoldLearning - A Julia package for manifold learning and nonlinear dimensionality reduction.
      • Merlin - Flexible Deep Learning Framework in Julia.
      • ROCAnalysis - Receiver Operating Characteristics and functions for evaluation probabilistic binary classifiers.
      • GaussianMixtures - Large scale Gaussian Mixture Models.
      • ScikitLearn - Julia implementation of the scikit-learn API.
      • Knet - Koç University Deep Learning Framework.
      • MLJ - A Julia machine learning framework.
      • Topic Models - TopicModels for Julia. **[Deprecated]**
      • Text Analysis - Julia package for text analysis.
      • Word Tokenizers - Tokenizers for Natural Language Processing in Julia
      • Corpus Loaders - A Julia package providing a variety of loaders for various NLP corpora.
      • Embeddings - Functions and data dependencies for loading various word embeddings
      • Languages - Julia package for working with various human languages
      • WordNet - A Julia package for Princeton's WordNet
      • Graph Layout - Graph layout algorithms in pure Julia.
      • LightGraphs - Graph modelling and analysis.
      • Data Frames Meta - Metaprogramming tools for DataFrames.
      • Julia Data - library for working with tabular data in Julia. **[Deprecated]**
      • Data Read - Read files from Stata, SAS, and SPSS.
      • Hypothesis Tests - Hypothesis tests for Julia.
      • Gadfly - Crafty statistical graphics for Julia.
      • Stats - Statistical tests for Julia.
      • RDataSets - Julia package for loading many of the data sets available in R.
      • DataFrames - library for working with tabular data in Julia.
      • Distributions - A Julia package for probability distributions and associated functions.
      • Data Arrays - Data structures that allow missing values. **[Deprecated]**
      • Time Series - Time series toolkit for Julia.
      • Sampling - Basic sampling algorithms for Julia.
      • DSP - Digital Signal Processing (filtering, periodograms, spectrograms, window functions).
      • JuliaCon Presentations - Presentations for JuliaCon.
      • Images - An image library for Julia.
      • DataDeps - Reproducible data setup for reproducible science.
      • Mixed Models - A Julia package for fitting (statistical) mixed-effects models.
      • GLMNet - Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet.

  • Kotlin

    • [Tools](#tools-1)

      • KotlinDL - Deep learning framework written in Kotlin.

  • Lua

    • [Tools](#tools-1)

      • Torch7
      • Numeric Lua
      • Lunatic Python
      • Lua - Numerical Algorithms
      • Numeric Lua
      • Numeric Lua
      • autograd - Autograd automatically differentiates native Torch code. Inspired by the original Python version.
      • graph - Graph package for Torch. **[Deprecated]**
      • signal - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft.
      • nn - Neural Network package for Torch.
      • nngraph - This package provides graphical computation for nn library in Torch7.
      • nnx - A completely unstable and experimental package that extends Torch's builtin nn library.
      • rnn - A Recurrent Neural Network library that extends Torch's nn. RNNs, LSTMs, GRUs, BRNNs, BLSTMs, etc.
      • dpnn - Many useful features that aren't part of the main nn package.
      • dp - A deep learning library designed for streamlining research and development using the Torch7 distribution. It emphasizes flexibility through the elegant use of object-oriented design patterns. **[Deprecated]**
      • optim - An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
      • unsup - A package for unsupervised learning in Torch. Provides modules that are compatible with nn (LinearPsd, ConvPsd, AutoEncoder, ...), and self-contained algorithms (k-means, PCA). **[Deprecated]**
      • manifold - A package to manipulate manifolds.
      • svm - Torch-SVM library. **[Deprecated]**
      • lbfgs - FFI Wrapper for liblbfgs. **[Deprecated]**
      • vowpalwabbit - An old vowpalwabbit interface to torch. **[Deprecated]**
      • OpenGM - OpenGM is a C++ library for graphical modelling, and inference. The Lua bindings provide a simple way of describing graphs, from Lua, and then optimizing them with OpenGM. **[Deprecated]**
      • spaghetti - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu **[Deprecated]**
      • LuaSHKit - A Lua wrapper around the Locality sensitive hashing library SHKit **[Deprecated]**
      • kernel smoothing - KNN, kernel-weighted average, local linear regression smoothers. **[Deprecated]**
      • cutorch - Torch CUDA Implementation.
      • cunn - Torch CUDA Neural Network Implementation.
      • imgraph - An image/graph library for Torch. This package provides routines to construct graphs on images, segment them, build trees out of them, and convert them back to images. **[Deprecated]**
      • videograph - A video/graph library for Torch. This package provides routines to construct graphs on videos, segment them, build trees out of them, and convert them back to videos. **[Deprecated]**
      • saliency - code and tools around integral images. A library for finding interest points based on fast integral histograms. **[Deprecated]**
      • stitch - allows us to use hugin to stitch images and apply same stitching to a video sequence. **[Deprecated]**
      • sfm - A bundle adjustment/structure from motion package. **[Deprecated]**
      • fex - A package for feature extraction in Torch. Provides SIFT and dSIFT modules. **[Deprecated]**
Programming Languages
Python 189 Julia 45 C++ 39 Go 37 JavaScript 33 Jupyter Notebook 33 Clojure 28 Scala 22 C 15 Java 14
Categories
Python 368 R 88 JavaScript 73 C++ 60 Julia 59 Java 50 Lua 47 Clojure 44 Go 42 Scala 33 Tools 26 Ruby 26 Matlab 17 .NET 14 SAS 12 Swift 12 C 8 Rust 8 Objective C 8 Books 7 Haskell 6 Common Lisp 5 Perl 5 PHP 5 OCaml 4 Elixir 4 TensorFlow 3 Perl 6 2 Crystal 2 Credits 2 Fortran 2 OpenCV 1 Erlang 1 Scheme 1 Kotlin 1 APL 1
Sub Categories
General-Purpose Machine Learning 607 [Tools](#tools-1) 436 Data Analysis / Data Visualization 2 Natural Language Processing 1 OpenSource-Computer-Vision 1
Keywords
machine-learning 208 python 118 deep-learning 84 data-science 70 pytorch 37 neural-network 30 nlp 29 scikit-learn 28 tensorflow 27 artificial-intelligence 24 natural-language-processing 21 julia 20 ml 20 statistics 18 neural-networks 18 clojure 18 java 17 ai 17 hyperparameter-optimization 15 go 14 regression 14 gpu 14 computer-vision 14 machine-learning-algorithms 13 visualization 13 data-mining 12 javascript 12 c-plus-plus 12 reinforcement-learning 12 data-analysis 12 random-forest 12 automl 12 big-data 11 golang 11 jupyter-notebook 11 keras 11 xgboost 11 scala 10 numpy 10 classification 10 jupyter 10 deep-neural-networks 10 r 9 spark 9 distributed 8 feature-engineering 8 ruby 8 automated-machine-learning 8 machinelearning 8 machine-learning-library 8