Awesome Machine Learning
by josephmisiti · josephmisiti/awesome-machine-learning
ML frameworks, libraries and software by language.
DThis book teaches you how to take machine learning models from your personal laptop to large distributed clusters. You’ll explore key concepts and patterns behind successful distributed machine learning systems, and learn technologies like TensorFlow, Kubernetes, Kubeflow, and Argo Workflows directly from a key maintainer and contributor, with real-world scenarios and hands-on projects.
Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.
HThrough a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent syste
Learn the essentials of machine learning by completing a carefully designed set of real-world projects.
This blog provides a curated list of introductory books to help aspiring ML professionals to grasp foundational machine learning concepts and techniques.
An opensource viewer for neural network, deep learning and machine learning models
Free, no-signup APIs for text, image, and audio generation with no API keys required. Offers OpenAI-compatible interfaces and React hooks for easy integration.
Train Machine Learning models on the fly to recognize your own images, sounds, & poses.
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.
AА 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.
C
Cas known as L0CV, is a new generation of computer vision open source online learning media, a cross-platform interactive learning framework integrating graphics, source code and HTML. the L0CV ecosystem — Notebook, Datasets, Source Code, and from Diving-in to Advanced — as well as the L0CV Hub.
MATLAB source code that implements the contourlet transform and its utility functions.
The Curvelet transform is a higher dimensional generalization of the Wavelet transform designed to represent images at different scales and different angles.
DA PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
DA lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for Python covering cutting-edge models such as VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, Dlib and ArcFace.
D
DFAIR's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework. [Deprecated]
DFAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.
DLib has C++ and Python interfaces for face detection and training general object detectors.
DEasy to install and use deep learning Faster R-CNN face detection for images and video in a docker container. [Deprecated]
DA PyTorch implementation of DeepDream. Allows individuals to quickly and easily train their own custom GoogleNet models with custom datasets for DeepDream.
Eblearn is an object-oriented C++ library that implements various machine learning models [Deprecated]
Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.
Eface recognition system that can be easily integrated into any system without prior machine learning skills. CompreFace provides REST API for face recognition, face verification, face detection, face mask detection, landmark detection, age, and gender recognition and is easily deployed with docker.
FFace recognition library that recognizes and manipulates faces from Python or from the command line.
Free production platform for text-to-image generation using Nano Banana V2 model.
IA library containing Convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
ILight face detection and recognition system with huge possibilities, based on Microsoft Face API and TensorFlow made for small IoT devices like raspberry pi.
JGenerative AI Image Toolset with GANs and Diffusion for Real-World Applications.
L
LPretrain computer vision models on unlabeled data for industrial applications
LCollection and a development kit of MATLAB mex functions for OpenCV library.
MMLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.
NA PyTorch implementation of Justin Johnson's neural-style (neural style transfer).
OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
OA real-time multi-person keypoint detection library for body, face, hands, and foot estimation
O
P
PPython-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded in images. Python-tesseract is a wrapper for Google's Tesseract-OCR Engine.
PRdeep learning based cutting-edge facial detector for Python coming with facial landmarks
S
SSwarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm, Artificial Fish Swarm Algorithm in Python)
SA TensorFlow Keras-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.
SA PyTorch-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.
An open source computer vision framework that gives access to several high-powered computer vision libraries, such as OpenCV. Written on Python and runs on Mac, Windows, and Ubuntu Linux.
TTF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs).
TPyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more.
VVIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.
VLFeat is an open and portable library of computer vision algorithms, which has a Matlab toolbox.
YUltralytics' YOLOv8 implementation with C++ support for real-time object detection and tracking, optimized for edge devices.
G
G
V
GIncanter is a Clojure-based, R-like platform for statistical computing and graphics.
P
P
TA dataframe grammar wrapping tech.ml.dataset, inspired by several R libraries
TClojure dataframe library and pipeline for data processing and machine learning
A
A
AAutoViz performs automatic visualization of any dataset with a single line of Python code. Give it any input file (CSV, txt or JSON) of any size and AutoViz will visualize it. See Medium article .
BCPU and GPU-accelerated matrix library intended to support large-scale exploratory data analysis.
B
B
B
BA dashboard library for interactive visualizations using flask socketio and react.
BCartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.
C
D
DA framework for creating analytical web applications built on top of Plotly.js, React, and Flask
D
D
D
DSource code and supporting content for my Ruby Manor presentation on Data Visualisation with Ruby. [Deprecated]
DA library to compare Pandas, Polars, and Spark data frames. It provides stats and lets users adjust for match accuracy.
D
DMathematics software for numeric computation, statistics, symbolic calculations, data analysis and data visualization.
DA GitHub Repository Where you can Learn Datavisualizatoin Basics to Intermediate level.
DA little logger for machine learning research. Output any object to the terminal, CSV, TensorBoard, text logs on disk, and more with just one call to logger.log().
E
FIgnite your models into blazing-fast machine learning APIs with a modern framework.
GEfficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.
G
G
G
G
G
G
G
G
H
I
I
J
K
LA workflow engine for solving machine learning problems by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation via user-defined (Python) functions.
L
LLime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.
MA tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.
Numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and everyday use. Supports .Net 4.0, .Net 3.5 and Mono on Windows, Linux and Mac; Silverlight 5, WindowsPhone/SL 8, WindowsPhone 8.1 and Windows 8 with PCL Portable Profiles 47 and 344; Android/iOS with Xamarin.
NN-dimensional arrays in Scala 3. Think NumPy ndarray, but with compile-time type-checking/inference over shapes, tensor/axis labels & numeric data types
Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
numl is a machine learning library intended to ease the use of using standard modelling techniques for both prediction and clustering.
NAn all-in-one NuPIC Hierarchical Temporal Memory visualization and debugging super-tool! [Deprecated]
ODistributed, masterless, high performance, fault tolerant data processing. Written entirely in Clojure.
OA library providing high-performance, easy-to-use data structures and data analysis tools.
P, a pluggable architecture for data and image processing, which can
PTools for writing, submitting, debugging, and monitoring Storm topologies in pure Python.
P
PPredictionIO, a machine learning server for software developers and data engineers.
PPyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters
PSimple plotting for Python. Wrapper for D3xterjs; easily render charts in-browser.
Short for Python Dynamics, used to assist with workflow in the modelling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
P
P
R
Rgnuplot wrapper for Ruby, especially for plotting ROC curves into SVG files. [Deprecated]
S
SA visualization library for quick and easy generation of common plots in data analysis and machine learning.
A Python-based ecosystem of open-source software for mathematics, science, and engineering.
SSho is an interactive environment for data analysis and scientific computing that lets you seamlessly connect scripts (in IronPython) with compiled code (in .NET) to enable fast and flexible prototyping. The environment includes powerful and efficient libraries for linear algebra as well as data visualization that can be used from any .NET language, as well as a feature-rich interactive shell for rapid development.
SMassively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters, has python API.
S
S
S
SSA data exploration platform designed to be visual, intuitive, and interactive.
S
S
TDebugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training.
FREE! Includes all SAS packages necessary for data analysis and visualization, and includes online SAS courses.
VA high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. Documentation can be found here.
V
V
W
X
Zdata.table provides a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use, convenience and programming speed.
A data manipulation package that helps to solve the most common data manipulation problems.
is the basis for truly interactive displays and dashboards in R. However, some measure of interactivity can be achieved with htmlwidgets bringing javascript libraries to R. These include, plotly, dygraphs, highcharter, and several others.
and quanteda are the main packages for managing, analyzing, and visualizing textual data.
for visualizing geospatial data with static maps and leaflet for interactive maps
CA Jupyter kernel for Clojure - run Clojure code in Jupyter Lab, Notebook and Console.
DA listener that streams your spark events logs to delight, a free and improved spark UI
E
HClojure(Script) library and framework for creating interactive visualization applications based in Vega-Lite (VGL) and/or Vega (VG) specifications. Automatic framing and layouts along with a powerful templating system for abstracting visualization specs
OData visualisation using Vega/Vega-Lite and Hiccup, and a live-reload platform for literate-programming
PA Clojure/Clojurescript notebook application/-library based on Gorilla-REPL
SClojure(Script) client/server application for dynamic interactive explorations and the creation of live shareable documents capturing them using Vega/Vega-Lite, CodeMirror, markdown, and LaTeX
BBurn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals
C
D
DDeep 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.
D
D
D
F
JFriendly guide on using Keras to implement a simple Neural Network in Python.
K
T
AScripts to generate a dataset with static frames from the Arcade Learning Environment.
C
DLibrary of SAS Enterprise Miner process flow diagrams to help you learn by example about specific data mining topics.
EExample code and materials that illustrate applications of SAS machine learning techniques.
EExample code and materials that illustrate using neural networks with several hidden layers in SAS.
EExample code and materials that illustrate techniques for integrating SAS with other analytics technologies in Java, PMML, Python and R.
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 trained in the browser with TensorFlow.js
TExample of how the neural network learns to predict the angle between two points created with Synaptic.
T
TInteractive visualizations explaining neural networks, backpropagation, attention mechanisms, and transformers.
A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language.
A federated learning framework for machine learning and other computations on decentralized data.
1The Accord.NET Framework is a complete framework for building machine learning, computer vision, computer audition, signal processing and statistical applications.
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.
AA genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.
AA bounded controller for production ML under distribution shift — detects drift, learns from delayed labels, and takes the smallest safe steering step to defer unnecessary retrains.
AA machine learning library by Airbnb designed from the ground up to be human friendly.
AIn-context learning framework that allows agents to learn from execution feedback.
ahaz: Regularization for semiparametric additive hazards regression. [Deprecated]
A
AA 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
AFrom-scratch Go port of tinygrad: a graph-rewrite ML compiler with reverse-mode autodiff and a WebGPU backend.
AAn Apache Incubating project for developing an open source machine learning library.
AAutomated machine learning, data formatting, ensembling, and hyperparameter optimization for competitions and exploration- just give it a .csv file! [Deprecated]
ADrop-in AsyncOpenAI replacement that transparently batches requests via the Batch API for cheaper LLM inference.
A
AAutograd automatically differentiates native Torch code. Inspired by the original Python version.
AAutomated machine learning for production and analytics. Lets you focus on the fun parts of ML, while outputting production-ready code, and detailed analytics of your dataset and results. Includes support for NLP, XGBoost, CatBoost, LightGBM, and soon, deep learning.
AA tutorial to help machine learning researchers to automatically obtain optimized machine learning models with the optimal learning performance on any specific task.
A> Automatically Build Variant Interpretable ML models fast! AutoViML is pronounced "auto vimal", is a comprehensive and scalable Python AutoML toolkit with imbalanced handling, ensembling, stacking and built-in feature selection. Featured in Medium article .
A
A
A
A
A
BBackprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
B
B
BBook/iPython notebooks on Probabilistic Programming in Python.
B
B
BFast Neural Networks framework built on top of Metal. Supports TensorFlow models.
BToolkit for package and deploy machine learning models for serving in production
B
B
B
BIt implemented 3 layers of neural networks ( Input Layer, Hidden Layer and Output Layer ) and it was named Back Propagation Neural Networks (BPN). This network can be used in products recommendation, user behavior analysis, data mining and data analysis. [Deprecated]
B
B
B
B
B
B
B
CA deep learning framework developed with cleanliness, readability, and speed in mind. [DEEP LEARNING]
CCandle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.
CA general classifier module to allow Bayesian and other types of classifications.
Classification and Regression Training: Unified interface to ~150 ML algorithms in R.
caretEnsemble: Framework for fitting multiple caret models as well as creating ensembles of such models. [Deprecated]
CHigh-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing. Being able to research/develop something new, rather than write another regular train loop.
CGeneral purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
CTorch-like deep learning framework for Javascript with support for tensors, autograd, optimizers, and other neural net constructs.
CCephes mathematical functions library, wrapped for Torch. Provides and wraps the 180+ special mathematical functions from the Cephes mathematical library, developed by Stephen L. Moshier. It is used, among many other places, at the heart of SciPy. [Deprecated]
CCa lightweight decision tree framework for Python with categorical feature support covering regular decision tree algorithms such as ID3, C4.5, CART, CHAID and regression tree; also some advanced bagging and boosting techniques such as gradient boosting, random forest and adaboost.
C
CA Java library for genetic algorithms, evolutionary computation, and stochastic local search, with a focus on self-adaptation / self-tuning, as well as parallel execution.
COnline learning algorithms (Perceptron, AROW, SCW, Logistic Regression).
CThe standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
CAuto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution.
C
CThe Push programming language and the PushGP genetic programming system implemented in Clojure.
CGeneral Machine Learning library using Numenta’s Cortical Learning Algorithm. [Deprecated]
C
CAgglomerative hierarchical clustering implemented in JavaScript for Node.js and the browser. [Deprecated]
CClustering algorithms implemented in JavaScript for Node.js and the browser. [Deprecated]
CThe Computational Network Toolkit (CNTK) by Microsoft Research, is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph.
CA Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.
CAn open-source deep learning system for large-scale model training and inference with high efficiency and low cost.
CThe best-in-class MLOps platform with experiment tracking, model production monitoring, a model registry, and data lineage from training straight through to production.
CFunctionally composable Machine Learning library using Numenta’s Cortical Learning Algorithm. [Deprecated]
C
CAn ONNX runtime written in pure C (99) with zero dependencies focused on small embedded devices. Run inference on your machine learning models no matter which framework you train it with. Easy to install and compiles everywhere, even in very old devices.
ConvNetJS is a JavaScript library for training Deep Learning models[DEEP LEARNING] [Deprecated]
CORElearn: Classification, regression, feature evaluation and ordinal evaluation.
CA comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data.
C
CUnified interface for constructing and managing machine learning workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
CPython implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree [Deprecated]
C
CModel Context Protocol server that exposes Creatify AI's video generation capabilities to AI assistants, enabling natural language video creation workflows.
C
D
DDarknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
DMachine Learning framework for rapid development of Machine Learning and Statistical applications.
D
D
DNodeJS Implementation of Decision Tree using ID3 Algorithm. [Deprecated]
DValidation & testing of machine learning models and data during model development, deployment, and production. This includes checks and suites related to various types of issues, such as model performance, data integrity, distribution mismatches, and more.
DA machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.
Ddeeplearn-rs provides simple networks that use matrix multiplication, addition, and ReLU under the MIT license.
Creating statically typed dynamic neural networks from object-oriented & functional programming constructs.
D
DScalable deep learning training platform, including integrated support for distributed training, hyperparameter tuning, experiment tracking, and model management.
An automatic differentiation (AD) library providing exact and efficient derivatives (gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) for machine learning and optimization applications. Operations can be nested to any level, meaning that you can compute exact higher-order derivatives and differentiate functions that are internally making use of differentiation, for applications such as hyperparameter optimization.
DThe Deep Learning GPU Training System (DIGITS) is a web application for training deep learning models.
DA distributed machine learning (parameter server) framework by Microsoft. Enables training models on large data sets across multiple machines. Current tools bundled with it include: LightLDA and Distributed (Multisense) Word Embedding.
D
D
DAn in-memory machine learning library built on top of Breeze. It provides immutable objects and exposes its functionality through a scikit-learn-like API.
DA 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]
DA software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.
DHigh performance library for time series distances (DTW) and time series clustering.
D
DA dynamic neural network library working well with networks that have dynamic structures that change for every training instance. Written in C++ with bindings in Python.
EA library for probabilistic modelling, inference, and criticism. Built on top of TensorFlow.
EElemStatLearn: Data sets, functions and examples from the book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman.
Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)
EAn advanced neural network and machine learning framework. Encog contains classes to create a wide variety of networks, as well as support classes to normalize and process data for these neural networks. Encog trains using multithreaded resilient propagation. Encog can also make use of a GPU to further speed processing time. A GUI based workbench is also provided to help model and train neural networks.
EClojure wrapper for Encog (v3) (Machine-Learning framework that specializes in neural-nets). [Deprecated]
EAn advanced neural network and machine learning framework. Encog contains classes to create a wide variety of networks, as well as support classes to normalize and process data for these neural networks. Encog trainings using multithreaded resilient propagation. Encog can also make use of a GPU to further speed processing time. A GUI based workbench is also provided to help model and train neural networks.
Data mining and machine learning that creates deployable models using a GUI or code.
EEurybia monitors data and model drift over time and securizes model deployment with data validation.
EInteractive reports to analyze machine learning models during validation or production monitoring.
EAutomatically creates deployable machine learning models across numerous market or customer segments using a GUI.
FHigh-level wrapper built on the top of Pytorch which supports vision, text, tabular data and collaborative filtering.
FA feature store for the management, discovery, and access of machine learning features. Feast provides a consistent view of feature data for both model training and model serving.
FOpen source library with an exhaustive battery of feature engineering and selection methods based on pandas and scikit-learn.
FA set of tools for creating and testing machine learning features, with a scikit-learn compatible API.
FA library for automated feature engineering. It excels at transforming transactional and relational datasets into feature matrices for machine learning using reusable feature engineering "primitives".
FAn AutoML framework for the automated design of composite modelling pipelines. It can handle classification, regression, and time series forecasting tasks on different types of data (including multi-modal datasets).
FA package for feature extraction in Torch. Provides SIFT and dSIFT modules. [Deprecated]
FA highly-modular C++ machine learning library for embedded electronics and robotics.
F
Fforecast: Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models.
forecastHybrid: Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the "forecast" package.
frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks. [Deprecated]
FFrouros is an open source Python library for drift detection in machine learning systems.
FSimple machine learning library, including Perceptron, Regression, Support Vector Machine, Decision Tree and more, it's easy to use and easy to learn for beginners.
FGAMBoost: Generalized linear and additive models by likelihood based boosting. [Deprecated]
G
GUnsupervised machine learning with multivariate Gaussian mixture model.
G
GMulti-platform genetic algorithm library for .NET Core and .NET Framework. The library has several implementations of GA operators, like: selection, crossover, mutation, reinsertion and termination.
G
Gglmpath: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model.
GMMBoost: Likelihood-based Boosting for Generalized mixed models. [Deprecated]
G
GFast and convenient feature processing for low latency machine learning in Go.
G
GLinear / Logistic regression, Neural Networks, Collaborative Filtering and Gaussian Multivariate Distribution. [Deprecated]
G
GGo binding for MXNet cpredictapi to do inference with a pre-trained model.
G
GA page of content on TensorFlow, including academic papers and links to related topics.
G
G
GGoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN. [Deprecated]
G
G
GAn offline recommender system backend based on collaborative filtering written in Go.
GThe Fastest Gower Distance Implementation for Python. GPU-accelerated similarity matching for mixed data types, 15-25% faster than alternatives with production-ready reliability.
GA Python library for quickly creating and sharing demos of models. Debug models interactively in your browser, get feedback from collaborators, and generate public links without deploying anything.
A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame.
grpreg: Regularization paths for regression models with grouped covariates.
A framework for fast, parallel, and distributed machine learning algorithms at scale -- Deeplearning, Random forests, GBM, KMeans, PCA, GLM.
HML engine that supports distributed learning on Hadoop, Spark or your laptop via APIs in R, Python, Scala, REST/JSON.
H
Ha suite of libraries for interpreting machine learning models according to their algebraic structure. [Deprecated]
H
HA data-intensive platform for AI with the industry's first open-source feature store. The Hopsworks Feature Store provides both a feature warehouse for training and batch based on Apache Hive and a feature serving database, based on MySQL Cluster, for online applications.
HFastest unstructured dataset management for TensorFlow/PyTorch. Stream & version-control data. Store even petabyte-scale data in a single numpy-like array on the cloud accessible on any machine. Visit activeloop.ai for more info.
HA hybrid recommender system based upon scikit-learn algorithms. [Deprecated]
Ha service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.
I> A delightful machine learning tool that allows you to train/fit, test and use models without writing code
IImplementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING]
IPython toolbox for quick implementation, modification, evaluation, and visualization of ensemble learning algorithms for class-imbalanced data. Supports out-of-the-box multi-class imbalanced (long-tailed) classification.
Python module to perform under sampling and oversampling with various techniques.
IAn 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]
Infer.NET is a framework for running Bayesian inference in graphical models. One can use Infer.NET to solve many different kinds of machine learning problems, from standard problems like classification, recommendation or clustering through customized solutions to domain-specific problems. Infer.NET has been used in a wide variety of domains including information retrieval, bioinformatics, epidemiology, vision, and many others.
IA seamless way to speed up your Scikit-learn applications with no accuracy loss and code changes.
IA high performance software library developed by Intel and optimized for Intel's architectures. Library provides algorithmic building blocks for all stages of data analytics and allows to process data in batch, online and distributed modes.
IInterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations.
IA distributed Spark/Scala implementation of the isolation forest algorithm for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.
JJAX is Autograd and XLA, brought together for high-performance machine learning research.
JJRuby Mahout is a gem that unleashes the power of Apache Mahout in the world of JRuby. [Deprecated]
JA Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.
JMachine learning toolkit with classification and clustering for Node.js; supports visualization (see visualml.io).
K
KA JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
K> An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.
K
KA python package that integrates an LLM copilot inside the keras model development workflow.
K
KKNN, kernel-weighted average, local linear regression smoothers. [Deprecated]
KSimple JavaScript implementation of the k-means algorithm, for node.js and the browser. [Deprecated]
KJavaScript implementation of the k nearest neighbors algorithm for supervised learning.
K
KJust a simple implementation of K-Nearest Neighbors algorithm using with a bunch of similarity measures.
KIt implemented Fuzzy C-Means (FCM) the fuzzy clustering / classification algorithm on Machine Learning. It could be used in data mining and image compression. [Deprecated]
KIt is a non-supervisory and self-learning algorithm (adjust the weights) in the neural network of Machine Learning. [Deprecated]
KIt implemented K-Means clustering and classification algorithm. It could be used in data mining and image compression. [Deprecated]
LSimple, concise implementations of machine learning techniques and utilities in Clojure.
L
L
LLearning 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.
L
Lopen source framework for machine intelligence, sharing concepts from TensorFlow and Caffe. Available under the MIT license. [[Deprecated]](https://medium.com/@mjhirn/tensorflow-wins-89b78b29aafb#.s0a3uy4cc)
LJavaScript implementation of logistic regression/c4.5 decision tree [Deprecated]
LA pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
LA generic approach that allows to mimic most factorization models by feature engineering.
LiblineaR: Linear Predictive Models Based On The Liblinear C/C++ Library.
L
LA lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
Algorithms for learning and inference with discrete probabilistic models.
A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.
LMicrosoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
LA Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with objective to build predictive models with one line of code.
LL> A graph sampling extension library for NetworkX with a Scikit-Learn like API.
LA header-only C++11 Neural Network library. Low dependency, native traditional chinese document.
LA Lua wrapper around the Locality sensitive hashing library SHKit [Deprecated]
L
M
Mautomated build consisting of a web-interface, and set of programmatic-interface API, for support vector machines. Corresponding dataset(s) are stored into a SQL database, then generated model(s) used for prediction(s), are stored into a NoSQL datastore.
MExamples of popular machine learning algorithms (neural networks, linear/logistic regressions, K-Means, etc.) with code examples and mathematics behind them being explained.
M
M
M
MAn Objective-C multilayer perceptron library, with full support for training through backpropagation. Implemented using vDSP and vecLib, it's 20 times faster than its Java equivalent. Includes sample code for use from Swift.
M
M
MA Julia package for manifold learning and nonlinear dimensionality reduction.
MA production-ready library for multicalibration, fairness, and bias correction in machine learning models.
M
MUniversal memory service with semantic search, autonomous consolidation, and multi-client support for AI applications.
An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
M
M
MNeural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes.
MMExamples and best practices for building recommendation systems, provided as Jupyter notebooks. The repo contains some of the latest state of the art algorithms from Microsoft Research as well as from other companies and institutions.
M
M
MAn asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
MM> A Repository Containing Classification, Clustering, Regression, Recommender Notebooks with illustration to make them.
MImplementations of Machine Learning models from scratch in Python with a focus on transparency. Aims to showcase the nuts and bolts of ML in an accessible way.
M
MML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more.
MThe Machine Learning Database is a database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.
MA high performance, memory efficient, maximally parallelized ensemble learning, integrated with scikit-learn.
MLightweight ML utility for automated training, evaluation, and prediction with CLI and Python API support.
M
MAn Automated Machine Learning (AutoML) python package for tabular data. It can handle: Binary Classification, MultiClass Classification and Regression. It provides explanations and markdown reports.
MA simple Machine Learning Framework written in Swift. Currently features Simple Linear Regression, Polynomial Regression, and Ridge Regression.
MFast multilayer perceptron neural network library for iOS and Mac OS X. MLPNeuralNet predicts new examples by trained neural networks. It is built on top of the Apple's Accelerate Framework, using vectorized operations and hardware acceleration if available. [Deprecated]
MA library consisting of useful tools for data science and machine learning tasks.
M
MMIt implemented multi-perceptrons neural network (ニューラルネットワーク) based on Back Propagation Neural Networks (BPN) and designed unlimited-hidden-layers.
MLightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.
MLightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.
M.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/
NCEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms
N
NPython library capable of fully capturing the impact of data drift on performance. Allows estimation of post-deployment model performance without access to targets.
ncvreg: Regularization paths for SCAD- and MCP-penalized regression models.
NPlug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT). [Deprecated]
NNervana's high-performance Python-based Deep Learning framework [DEEP LEARNING]. [Deprecated]
Nneonrvm is an open source machine learning library based on RVM technique. It's written in C programming language and comes with Python programming language bindings.
N
NDBMS management system and designer for neural networks. The designer application is developed using WPF, and is a user interface which allows you to design your neural network, query the network, create and configure chat bots that are capable of asking questions and learning from your feedback. The chat bots can even scrape the internet for information to return in their output as well as to use for learning.
NCode samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
N
NC++ Neural Network library for Node.js. It has advantage on large dataset and multi-threaded training. [Deprecated]
NA framework providing the right abstractions to ease research, development, and deployment of your ML pipelines.
N
NEnterprise-grade LLM integration framework for building production-ready AI applications with built-in hallucination prevention, RAG, and MCP support.
NAimed at novice machine learners and non-expert programmers, this package offers easy (no coding needed) and comprehensive machine learning (evaluation and full report of predictive performance WITHOUT requiring you to code) in Python for NeuroImaging and any other type of features. This is aimed at absorbing much of the ML workflow, unlike other packages like nilearn and pymvpa, which require you to learn their API and code to produce anything useful.
N
Nnnet: Feed-forward Neural Networks and Multinomial Log-Linear Models. [Deprecated]
NA completely unstable and experimental package that extends Torch's builtin nn library.
NFANN (Fast Artificial Neural Network Library) bindings for Node.js [Deprecated]
N
N
N
OA python machine learning library created to combine powefull data analasys features with tensors and machine learning components, while maintaining support for other libraries.
OA low-level Linear Regression Engine utilizing the Ordinary Least Squares (OLS) method and QR decomposition.
OOpen source AI infrastructure layer. Eight agents run automatically: security, caching, memory, hallucination detection, and tamper-proof audit trail. Runs locally.
OOAn open-source cross-platform performance library for deep learning applications.
O
OA lightweight C library for ONNX model inference, optimized for performance and portability across platforms.
OAn ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).
OOpenGM 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]
OA PyTorch-based framework to train and validate the models producing high-quality embeddings.
OEvaluate, trace, test, and ship LLM applications across your dev and production lifecycles.
Open source engineering platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. (Source Code)
OAn optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
OOptuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
A library dedicated to automated hyperparameter optimization with a simple, lightweight API to facilitate drop-in replacement of grid search. Optunity is written in Python but interfaces seamlessly with MATLAB.
OLambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.
O
PA general-purpose library with C/C++ interface for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found here.
PParris, the automated infrastructure setup tool for machine learning algorithms.
P
PThis package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
PA complete object-oriented environment for machine learning in Matlab.
Ppenalized: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model.
penalizedLDA: Penalized classification using Fisher's linear discriminant. [Deprecated]
PSwift Language Bindings of TensorFlow. Using native TensorFlow models on both macOS / Linux.
PUncover insights, surface problems, monitor and fine tune your generative LLM, CV and tabular models.
Machine Learning library for PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
P
PHidden Markov Models for Python, implemented in Cython for speed and efficiency.
PA library for machine learning that builds predictions using a linear regression.
PA library for machine learning that builds predictions using a linear regression.
PA general-purpose network embedding framework: pair-wise representations optimization Network Edit.
P
P
PAn open-source, low-code machine learning library in Python that automates machine learning workflows.
P
P
PPeer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft
Plibrary for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.
P
P> Python Outlier Detection, comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. Featured for Advanced models, including Neural Networks/Deep Learning and Outlier Ensembles.
PA Python library for secure and private Deep Learning built on PyTorch and TensorFlow.
P
PA Python extension module wrapping the full TiMBL C++ programming interface. Timbl is an elaborate k-Nearest Neighbours machine learning toolkit.
P
PP> A temporal extension of PyTorch Geometric for dynamic graph representation learning.
PToolbox of models, callbacks, and datasets for AI/ML researchers.
A C library implementing the rudiments of a toolchain for working with adaptive probabilistic assembler programs.
A relational column-oriented database designed for real-time analytics on time series and event data.
randomForest: Breiman and Cutler's random forests for classification and regression.
randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
RAI-powered tools and applications for developers and businesses to enhance productivity and workflow automation. XAD -> Fast and easy-to-use backpropagation tool.
RRuby language bindings for LIBSVM which is a Library for Support Vector Machines.
rdetools: Relevant Dimension Estimation (RDE) in Feature Spaces. [Deprecated]
RA C library for product recommendations/suggestions using collaborative filtering (CF).
REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data. [Deprecated]
RAlgorithms for regression analysis (e.g. linear regression and logistic regression). [Deprecated]
Ran IPython-based environment for conducting data-driven research in a consistent and reproducible way. REP is not trying to substitute scikit-learn, but extends it and provides better user experience. [Deprecated]
R
R
RRmalschains: Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R.
rminer: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression. [Deprecated]
RA Recurrent Neural Network library that extends Torch's nn. RNNs, LSTMs, GRUs, BRNNs, BLSTMs, etc.
RReceiver Operating Characteristics and functions for evaluation probabilistic binary classifiers.
A modular scientific software framework. It provides all the functionalities needed to deal with big data processing, statistical analysis, visualization and storage.
RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories. [Deprecated]
RSNNS: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS).
RA high-level machine learning (ML) library that lets you build programs that learn from data using the PHP language.
RSome Machine Learning algorithms, implemented in Ruby. [Deprecated]
R
R
Ra machine learning framework featuring logistic regression, support vector machines, decision trees and random forests.
R
RRXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression.
Scode and tools around integral images. A library for finding interest points based on fast integral histograms. [Deprecated]
SAMOA is a framework that includes distributed machine learning for data streams with an interface to plug-in different stream processing platforms.
SA idiomatic Clojure machine learning library based on tech.ml.dataset with a unique approach for immutable data processing pipelines.
SA machine learning framework for multi-output/multi-label and stream data.
S
Ssda: Shrinkage Discriminant Analysis and CAT Score Variable Selection. [Deprecated]
SNode.js library with support for both simple and multiple linear regression. [Deprecated]
SShapash is a Python library that provides several types of visualization that display explicit labels that everyone can understand.
S> A data-driven framework to quantify the value of classifiers in a machine learning ensemble.
S
S
S
SPython implementation of many of the artificial intelligence algorithms described in the book "Artificial Intelligence, a Modern Approach". It focuses on providing an easy to use, well documented and tested library.
S
SA Python library for Bayesian Evidential Learning (BEL) in order to estimate the uncertainty of a prediction.
SPython library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.
SAn AutoML package for hyperparameters tuning using evolutionary algorithms, with built-in callbacks, plotting, remote logging and more.
S
S
SSkrub is a Python library that eases preprocessing and feature engineering for machine learning on dataframes.
SA library for learning neural networks, has C-interface, net set in JSON. Written in C++ with bindings in Python, C++ and C#.
S
S
S
SSpearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012. [Deprecated]
spectralGraphTopology: Learning Graphs from Data via Spectral Constraints.
SAutomatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. [DEEP LEARNING]
The spider is intended to be a complete object orientated environment for machine learning in Matlab.
SImplementation of machine learning stacking technique as a handy library in Python.
A probabilistic programming language implementing full Bayesian statistical inference with Hamiltonian Monte Carlo sampling.
A classifier is a machine learning tool that will take data items and place them into one of k classes.
SMachine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.
S> Lightweight, Python library for fast and reproducible machine learning experimentation. Introduces a very simple interface that enables clean machine learning pipeline design.
S> Curated collection of the neural networks, transformers and models that make your machine learning work faster and more effective.
Sallows us to use hugin to stitch images and apply same stitching to a video sequence. [Deprecated]
S
S
SHighly optimized artificial intelligence and machine learning library written in Swift.
SThe first neural network / machine learning library written in Swift. This is a project for AI algorithms in Swift for iOS and OS X development. This project includes algorithms focused on Bayes theorem, neural networks, SVMs, Matrices, etc...