Ecosyste.ms: Awesome

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

Awesome Lists | Featured Topics | Projects

awesome-machine-learning

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

Last synced: 4 days ago
JSON representation

  • C

    • [Tools](#tools-1)

      • VLFeat - VLFeat is an open and portable library of computer vision algorithms, which has a Matlab toolbox.
      • Darknet - Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
      • Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF).
      • Hybrid Recommender System - A hybrid recommender system based upon scikit-learn algorithms. **[Deprecated]**
      • neonrvm - neonrvm 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.
      • cONNXr - An `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.
      • libonnx - A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
      • CCV - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.

  • Lua

  • R

    • General-Purpose Machine Learning

      • tm
      • ahaz - ahaz: Regularization for semiparametric additive hazards regression. **[Deprecated]**
      • arules - arules: Mining Association Rules and Frequent Itemsets
      • biglasso - biglasso: Extending Lasso Model Fitting to Big Data in R.
      • bmrm - bmrm: Bundle Methods for Regularized Risk Minimization Package.
      • Boruta - Boruta: A wrapper algorithm for all-relevant feature selection.
      • bst - bst: Gradient Boosting.
      • C50 - C50: C5.0 Decision Trees and Rule-Based Models.
      • caret - Classification and Regression Training: Unified interface to ~150 ML algorithms in R.
      • caretEnsemble - caretEnsemble: Framework for fitting multiple caret models as well as creating ensembles of such models. **[Deprecated]**
      • Clever Algorithms For Machine Learning
      • CORElearn - CORElearn: Classification, regression, feature evaluation and ordinal evaluation.
      • CoxBoost - CoxBoost: Cox models by likelihood based boosting for a single survival endpoint or competing risks **[Deprecated]**
      • Cubist - Cubist: Rule- and Instance-Based Regression Modelling.
      • e1071 - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien
      • earth - earth: Multivariate Adaptive Regression Spline Models
      • elasticnet - elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA.
      • ElemStatLearn - ElemStatLearn: 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.
      • evtree - evtree: Evolutionary Learning of Globally Optimal Trees.
      • forecast - forecast: Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models.
      • forecastHybrid - forecastHybrid: Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the "forecast" package.
      • fpc - fpc: Flexible procedures for clustering.
      • frbs - frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks. **[Deprecated]**
      • GAMBoost - GAMBoost: Generalized linear and additive models by likelihood based boosting. **[Deprecated]**
      • gamboostLSS - gamboostLSS: Boosting Methods for GAMLSS.
      • gbm - gbm: Generalized Boosted Regression Models.
      • glmnet - glmnet: Lasso and elastic-net regularized generalized linear models.
      • glmpath - glmpath: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model.
      • GMMBoost - GMMBoost: Likelihood-based Boosting for Generalized mixed models. **[Deprecated]**
      • grplasso - grplasso: Fitting user specified models with Group Lasso penalty.
      • grpreg - grpreg: Regularization paths for regression models with grouped covariates.
      • h2o - A framework for fast, parallel, and distributed machine learning algorithms at scale -- Deeplearning, Random forests, GBM, KMeans, PCA, GLM.
      • hda - hda: Heteroscedastic Discriminant Analysis. **[Deprecated]**
      • Introduction to Statistical Learning
      • ipred - ipred: Improved Predictors.
      • kernlab - kernlab: Kernel-based Machine Learning Lab.
      • klaR - klaR: Classification and visualization.
      • L0Learn - L0Learn: Fast algorithms for best subset selection.
      • lars - lars: Least Angle Regression, Lasso and Forward Stagewise. **[Deprecated]**
      • lasso2 - lasso2: L1 constrained estimation aka ‘lasso’.
      • LiblineaR - LiblineaR: Linear Predictive Models Based On The Liblinear C/C++ Library.
      • LogicReg - LogicReg: Logic Regression.
      • maptree - maptree: Mapping, pruning, and graphing tree models. **[Deprecated]**
      • mboost - mboost: Model-Based Boosting.
      • mlr - mlr: Machine Learning in R.
      • ncvreg - ncvreg: Regularization paths for SCAD- and MCP-penalized regression models.
      • nnet - nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models. **[Deprecated]**
      • pamr - pamr: Pam: prediction analysis for microarrays. **[Deprecated]**
      • party - party: A Laboratory for Recursive Partitioning
      • partykit - partykit: A Toolkit for Recursive Partitioning.
      • penalized - penalized: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model.
      • penalizedLDA - penalizedLDA: Penalized classification using Fisher's linear discriminant. **[Deprecated]**
      • penalizedSVM - penalizedSVM: Feature Selection SVM using penalty functions.
      • quantregForest - quantregForest: Quantile Regression Forests.
      • randomForest - randomForest: Breiman and Cutler's random forests for classification and regression.
      • randomForestSRC - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
      • rattle - rattle: Graphical user interface for data mining in R.
      • rda - rda: Shrunken Centroids Regularized Discriminant Analysis.
      • rdetools - rdetools: Relevant Dimension Estimation (RDE) in Feature Spaces. **[Deprecated]**
      • REEMtree - REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data. **[Deprecated]**
      • relaxo - relaxo: Relaxed Lasso. **[Deprecated]**
      • rgenoud - rgenoud: R version of GENetic Optimization Using Derivatives
      • Rmalschains - Rmalschains: Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R.
      • rminer - rminer: Simpler use of data mining methods (e.g. NN and SVM) in classification and regression. **[Deprecated]**
      • ROCR - ROCR: Visualizing the performance of scoring classifiers. **[Deprecated]**
      • RoughSets - RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories. **[Deprecated]**
      • rpart - rpart: Recursive Partitioning and Regression Trees.
      • RPMM - RPMM: Recursively Partitioned Mixture Model.
      • RSNNS - RSNNS: Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS).
      • RWeka - RWeka: R/Weka interface.
      • RXshrink - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression.
      • sda - sda: Shrinkage Discriminant Analysis and CAT Score Variable Selection. **[Deprecated]**
      • spectralGraphTopology - spectralGraphTopology: Learning Graphs from Data via Spectral Constraints.
      • svmpath - svmpath: svmpath: the SVM Path algorithm. **[Deprecated]**
      • tgp - tgp: Bayesian treed Gaussian process models. **[Deprecated]**
      • tree - tree: Classification and regression trees.
      • varSelRF - varSelRF: Variable selection using random forests.
      • XGBoost.R - R binding for eXtreme Gradient Boosting (Tree) Library.
      • igraph - binding to igraph library - General purpose graph library.
      • dplyr - A data manipulation package that helps to solve the most common data manipulation problems.
      • ggplot2 - A data visualization package based on the grammar of graphics.
      • tmap
      • Optunity - 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 to R.

  • SAS

    • General-Purpose Machine Learning

      • Factory Miner - Automatically creates deployable machine learning models across numerous market or customer segments using a GUI.
      • Enterprise Miner - Data mining and machine learning that creates deployable models using a GUI or code.
      • SAS/STAT - For conducting advanced statistical analysis.
      • Text Miner - Text mining using a GUI or code.
      • ML_Tables - Concise cheat sheets containing machine learning best practices.

  • C++

    • [Tools](#tools-1)

      • CUDA - This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]
      • VIGRA - VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.
      • Openpose - A real-time multi-person keypoint detection library for body, face, hands, and foot estimation
      • BanditLib - A simple Multi-armed Bandit library. **[Deprecated]**
      • Caffe - A deep learning framework developed with cleanliness, readability, and speed in mind. [DEEP LEARNING]
      • CatBoost - General 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.
      • CNTK - The 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.
      • DeepDetect - A 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.
      • DSSTNE - A software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.
      • DyNet - A 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.
      • Fido - A highly-modular C++ machine learning library for embedded electronics and robotics.
      • DLib - DLib has C++ and Python interfaces for face detection and training general object detectors.
      • Speedster - Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. [DEEP LEARNING]
      • Distributed Machine learning Tool Kit (DMTK) - A 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.
      • DLib - A suite of ML tools designed to be easy to imbed in other applications.
      • mlpack - A scalable C++ machine learning library.
      • PyCUDA - Python interface to CUDA
      • shark - A fast, modular, feature-rich open-source C++ machine learning library.
      • sofia-ml - Suite of fast incremental algorithms.
      • QuestDB - oriented database designed for real-time analytics on time series and event data.
      • CRFsuite - CRFsuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. **[Deprecated]**

  • APL

    • [Tools](#tools-1)

      • naive-apl - Naive Bayesian Classifier implementation in APL. **[Deprecated]**

  • Clojure

    • [Tools](#tools-1)

      • MXNet - Bindings to Apache MXNet - part of the MXNet project
      • Incanter - Incanter is a Clojure-based, R-like platform for statistical computing and graphics.
      • Java Interop - Clojure has Native Java Interop from which Java's ML ecosystem can be accessed
      • JavaScript Interop - ClojureScript has Native JavaScript Interop from which JavaScript's ML ecosystem can be accessed
      • Neanderthal - Fast Clojure Matrix Library (native CPU, GPU, OpenCL, CUDA)
      • Scicloj - Curated list of ML related resources for Clojure.

  • Fortran

    • [Tools](#tools-1)

  • Go

    • [Tools](#tools-1)

  • Java

    • [Tools](#tools-1)

      • Cortical.io - Retina: an API performing complex NLP operations (disambiguation, classification, streaming text filtering, etc...) as quickly and intuitively as the brain.
      • IRIS - [Cortical.io's](https://cortical.io) FREE NLP, Retina API Analysis Tool (written in JavaFX!) - [See the Tutorial Video](https://www.youtube.com/watch?v=CsF4pd7fGF0).
      • CoreNLP - Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words.
      • Stanford Parser - A natural language parser is a program that works out the grammatical structure of sentences.
      • Stanford POS Tagger - A Part-Of-Speech Tagger (POS Tagger).
      • Stanford Name Entity Recognizer - Stanford NER is a Java implementation of a Named Entity Recognizer.
      • Stanford Word Segmenter - Tokenization of raw text is a standard pre-processing step for many NLP tasks.
      • Tregex, Tsurgeon and Semgrex - Tregex is a utility for matching patterns in trees, based on tree relationships and regular expression matches on nodes (the name is short for "tree regular expressions").
      • Stanford Phrasal: A Phrase-Based Translation System
      • Stanford English Tokenizer - Stanford Phrasal is a state-of-the-art statistical phrase-based machine translation system, written in Java.
      • Stanford Tokens Regex - A tokenizer divides text into a sequence of tokens, which roughly correspond to "words".
      • Stanford Temporal Tagger - SUTime is a library for recognizing and normalizing time expressions.
      • Stanford SPIED - Learning entities from unlabeled text starting with seed sets using patterns in an iterative fashion.
      • Twitter Text Java - A Java implementation of Twitter's text processing library.
      • OpenNLP - a machine learning based toolkit for the processing of natural language text.
      • Apache cTAKES - 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.
      • 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.
      • Weka - Weka is a collection of machine learning algorithms for data mining tasks.
      • Storm - Storm is a distributed realtime computation system.
      • Keras Beginner Tutorial - Friendly guide on using Keras to implement a simple Neural Network in Python.

  • Scala

    • General-Purpose Machine Learning

      • FlinkML in Apache Flink - Distributed machine learning library in Flink.
      • Flink - Open source platform for distributed stream and batch data processing.
      • ScalaNLP - ScalaNLP is a suite of machine learning and numerical computing libraries.
      • DeepLearning.scala - Creating statically typed dynamic neural networks from object-oriented & functional programming constructs.
      • Smile - Statistical Machine Intelligence and Learning Engine.
      • MLlib in Apache Spark - Distributed machine learning library in Spark

  • 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.
      • TensorFlow.js - A WebGL accelerated, browser based JavaScript library for training and deploying ML models.
      • Rock Paper Scissors - Rock Paper Scissors trained in the browser with TensorFlow.js

  • Julia

    • [Tools](#tools-1)

      • Flux - Relax! Flux is the ML library that doesn't make you tensor

  • Matlab

    • [Tools](#tools-1)

      • Contourlets - MATLAB source code that implements the contourlet transform and its utility functions.
      • Curvelets - The Curvelet transform is a higher dimensional generalization of the Wavelet transform designed to represent images at different scales and different angles.
      • Bandlets - MATLAB code for bandlet transform.
      • Convolutional-Recursive Deep Learning for 3D Object Classification - Convolutional-Recursive Deep Learning for 3D Object Classification[DEEP LEARNING].
      • Spider - The spider is intended to be a complete object orientated environment for machine learning in Matlab.
      • LibSVM - A Library for Support Vector Machines.
      • LibLinear - A Library for Large Linear Classification.
      • matlab_bgl - MatlabBGL is a Matlab package for working with graphs.
      • gaimc - Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.
      • Shearlets - MATLAB code for shearlet transform.

  • .NET

    • [Tools](#tools-1)

      • OpenCVDotNet - A wrapper for the OpenCV project to be used with .NET applications.
      • Emgu CV - Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.
      • Accord-Framework - The Accord.NET Framework is a complete framework for building machine learning, computer vision, computer audition, signal processing and statistical applications.
      • Neural Network Designer - DBMS 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.
      • Sho - Sho 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.

  • Perl

  • PHP

    • General-Purpose Machine Learning

      • Rubix ML - A high-level machine learning (ML) library that lets you build programs that learn from data using the PHP language.

  • Python

    • General-Purpose Machine Learning

      • SimpleCV - 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.
      • Self-supervised learning
      • OpenVisionAPI - Open source computer vision API based on open source models.
      • NLTK - A leading platform for building Python programs to work with human language data.
      • BLLIP Parser - Python bindings for the BLLIP Natural Language Parser (also known as the Charniak-Johnson parser). **[Deprecated]**
      • editdistance - fast implementation of edit distance.
      • scikit-learn - A Python module for machine learning built on top of SciPy.
      • astroML - Machine Learning and Data Mining for Astronomy.
      • implicit - Fast Python Collaborative Filtering for Implicit Datasets.
      • LightFM - A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.
      • imbalanced-learn - Python module to perform under sampling and oversampling with various techniques.
      • Edward - A library for probabilistic modelling, inference, and criticism. Built on top of TensorFlow.
      • Cartopy - Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.
      • Numba - Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
      • igraph - binding to igraph library - General purpose graph library.
      • Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools.
      • PyDy - Short for Python Dynamics, used to assist with workflow in the modelling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
      • astropy - A community Python library for Astronomy.
      • matplotlib - A Python 2D plotting library.
      • cerebro2 - based visualization and debugging platform for NuPIC. **[Deprecated]**
      • Seaborn - A python visualization library based on matplotlib.
      • A gallery of interesting IPython notebooks
      • Python Programming for the Humanities - Course for Python programming for the Humanities, assuming no prior knowledge. Heavy focus on text processing / NLP.
      • Practical XGBoost in Python - comprehensive online course about using XGBoost in Python.
      • Machine Learning, Data Science and Deep Learning with Python - LiveVideo course that covers machine learning, Tensorflow, artificial intelligence, and neural networks.
      • Jina AI
      • Tensorflow-Federated
      • acme - An Open Source Distributed Framework for Reinforcement Learning that makes build and train your agents easily.

  • Ruby

    • General-Purpose Machine Learning

      • Awesome NLP with Ruby - Curated link list for practical natural language processing in Ruby.
      • Raspell - raspell is an interface binding for ruby. **[Deprecated]**
      • Twitter-text-rb - A library that does auto linking and extraction of usernames, lists and hashtags in tweets.
      • Awesome Machine Learning with Ruby - Curated list of ML related resources for Ruby.
      • ruby-plot - gnuplot wrapper for Ruby, especially for plotting ROC curves into SVG files. **[Deprecated]**
      • SciRuby

  • Swift

    • General-Purpose Machine Learning

      • Bender - Fast Neural Networks framework built on top of Metal. Supports TensorFlow models.
      • Swift AI - Highly optimized artificial intelligence and machine learning library written in Swift.
      • AIToolbox - 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.
      • Swift Brain - The 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...
      • Awesome Core ML Models - A curated list of machine learning models in CoreML format.

  • TensorFlow

    • General-Purpose Machine Learning

  • Tools

    • General-Purpose Machine Learning

      • Weaviate - technologies/weaviate) vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale.
      • MLReef - MLReef is an end-to-end development platform using the power of git to give structure and deep collaboration possibilities to the ML development process.
      • Pinecone - Vector database for applications that require real-time, scalable vector embedding and similarity search.
      • guild.ai - Tool to log, analyze, compare and "optimize" experiments. It's cross-platform and framework independent, and provided integrated visualizers such as tensorboard.
      • MLFlow - platform to manage the ML lifecycle, including experimentation, reproducibility and deployment. Framework and language agnostic, take a look at all the built-in integrations.
      • MachineLearningWithTensorFlow2ed - a book on general purpose machine learning techniques regression, classification, unsupervised clustering, reinforcement learning, auto encoders, convolutional neural networks, RNNs, LSTMs, using TensorFlow 1.14.1.
      • Pythonizr - An online tool to generate boilerplate machine learning code that uses scikit-learn.
      • Flyte - Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing.

  • Books

    • General-Purpose Machine Learning

      • Grokking Machine Learning - Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math.
      • Machine Learning Bookcamp - Learn the essentials of machine learning by completing a carefully designed set of real-world projects.
      • Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow - Through 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 systems.
      • Netron - An opensource viewer for neural network, deep learning and machine learning models
      • Teachable Machine - Train Machine Learning models on the fly to recognize your own images, sounds, & poses.
      • Model Zoo - Discover open source deep learning code and pretrained models.

  • Credits

  • Perl 6

  • Table of Contents

Programming Languages
C++ 8 C 6 Swift 4 Python 4 Ruby 2 Lua 1 HTML 1 APL 1
Categories
R 83 Python 28 Java 23 C++ 21 JavaScript 19 Matlab 10 Tools 8 C 8 Lua 7 Scala 6 Books 6 Clojure 6 Ruby 6 .NET 5 Swift 5 SAS 5 Perl 4 TensorFlow 2 Credits 2 APL 1 Go 1 Table of Contents 1 Perl 6 1 PHP 1 Julia 1 Fortran 1
Sub Categories
General-Purpose Machine Learning 156 [Tools](#tools-1) 103 Data Analysis / Data Visualization 1 Frameworks and Libraries 1
Keywords
machine-learning 16 deep-learning 7 python 4 awesome 4 neural-network 4 ruby 3 awesome-list 3 ios 3 swift 3 caffe 3 c 3 gpu 2 embedded 2 list 2 rubyml 2 rubynlp 2 deep-neural-networks 2 ml 2 apple 2 coreml 2 java 2 bayesian 2 onnx 2 tensorrt-inference 1 beta 1 r 1 tutorial 1 tensorrt-conversion 1 tensorrt 1 xgboost 1 c-plus-plus 1 rest-api 1 c-sharp 1 cntk 1 cognitive-toolkit 1 pytorch 1 object-detection 1 neural-nets 1 ncnn 1 distributed 1 image-segmentation 1 tsne 1 time-series 1 image-classification 1 image-search 1 computer-vision 1 cpp 1 cvpr-2017 1 face 1 foot-estimation 1