各大语言下的机器学习小汇总

主要参考josephmisiti提供的链接。语言方面主要集中在R、python、matlab等。 此外，reddit上也整理了很多资料。

目录

some usefull books

The following is a list of free, open source books on machine learning, statistics, data-mining, etc.

Machine-Learning / Data Mining

Naturual Language Processing

Probability & Statistics

Linear Algebra

A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php. Other awesome lists can be found in the awesome-awesomeness list.

Java

Natural Language Processing
  • [CoreNLP] (http://nlp.stanford.edu/software/corenlp.shtml) - 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] (http://nlp.stanford.edu/software/lex-parser.shtml) - A natural language parser is a program that works out the grammatical structure of sentences
  • [Stanford POS Tagger] (http://nlp.stanford.edu/software/tagger.shtml) - A Part-Of-Speech Tagger (POS Tagger
  • [Stanford Name Entity Recognizer] (http://nlp.stanford.edu/software/CRF-NER.shtml) - Stanford NER is a Java implementation of a Named Entity Recognizer.
  • [Stanford Word Segmenter] (http://nlp.stanford.edu/software/segmenter.shtml) - 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
  • Stanford Topic Modeling Toolbox - Topic modeling tools to social scientists and others who wish to perform analysis on datasets
  • Twitter Text Java - A Java implementation of Twitter’s text processing library
  • MALLET - A Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
  • OpenNLP - a machine learning based toolkit for the processing of natural language text.
  • 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.
  • 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.

General-Purpose Machine Learning

  • JSAT - Numerous Machine Learning algoirhtms for classification, regresion, and clustering.
  • MLlib in Apache Spark - Distributed machine learning library in Spark
  • Mahout - Distributed machine learning
  • 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
  • Meka - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
  • ORYX - Simple real-time large-scale machine learning infrastructure.
  • H2O - ML engine that supports distributed learning on data stored in HDFS.
  • WalnutiQ - object oriented model of the human brain
  • ELKI - Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)
  • Neuroph - Neuroph is lightweight Java neural network framework
  • java-deeplearning - Distributed Deep Learning Platform for Java, Clojure,Scala

Speech Recognition

  • CMU Sphinx - Open Source Toolkit For Speech Recognition purely based on Java speech recognition library.

Data Analysis / Data Visualization

  • Hadoop - Hadoop/HDFS
  • Spark - Spark is a fast and general engine for large-scale data processing.
  • Impala - Real-time Query for Hadoop

Julia

General-Purpose Machine Learning

  • 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)
  • Local Regression - Local regression, so smooooth!
  • Naive Bayes - Simple Naive Bayes implementation in Julia
  • Mixed Models - A Julia package for fitting (statistical) mixed-effects models
  • Simple MCMC - basic mcmc sampler implemented in Julia
  • Distance - Julia module for Distance evaluation
  • Decision Tree - Decision Tree Classifier and Regressor
  • Neural - A neural network in Julia
  • MCMC - MCMC tools for Julia
  • GLM - Generalized linear models in Julia
  • Online Learning
  • GLMNet - Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet
  • Clustering - Basic functions for clustering data: k-means, dp-means, etc.
  • SVM - SVM’s for Julia
  • Kernal Density - Kernel density estimators for julia
  • Dimensionality Reduction - Methods for dimensionality reduction
  • NMF - A Julia package for non-negative matrix factorization
  • ANN - Julia artificial neural networks

Natural Language Processing

Data Analysis / Data Visualization

  • Graph Layout - Graph layout algorithms in pure Julia
  • Data Frames Meta - Metaprogramming tools for DataFrames
  • Julia Data - library for working with tabular data in Julia
  • Data Read - Read files from Stata, SAS, and SPSS
  • Hypothesis Tests - Hypothesis tests for Julia
  • Gladfly - 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
  • Time Series - Time series toolkit for Julia
  • Sampling - Basic sampling algorithms for Julia

Misc Stuff / Presentations

Lua

General-Purpose Machine Learning

  • Torch7
    • cephes - Cephes 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.
    • graph - Graph package for Torch
    • randomkit - Numpy’s randomkit, wrapped for Torch

    • 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
    • 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).
    • manifold - A package to manipulate manifolds
    • svm - Torch-SVM library
    • lbfgs - FFI Wrapper for liblbfgs
    • vowpalwabbit - An old vowpalwabbit interface to torch.
    • OpenGM - OpenGM is a C++ library for graphical modeling, and inference. The Lua bindings provide a simple way of describing graphs, from Lua, and then optimizing them with OpenGM.
    • sphagetti - Spaghetti (sparse linear) module for torch7 by @MichaelMathieu
    • LuaSHKit - A lua wrapper around the Locality sensitive hashing library SHKit
    • kernel smoothing - KNN, kernel-weighted average, local linear regression smoothers
    • 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.
    • 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.
    • saliency - code and tools around integral images. A library for finding interest points based on fast integral histograms.
    • stitch - allows us to use hugin to stitch images and apply same stitching to a video sequence
    • sfm - A bundle adjustment/structure from motion package
    • fex - A package for feature extraction in Torch. Provides SIFT and dSIFT modules.
    • OverFeat - A state-of-the-art generic dense feature extractor
  • Numeric Lua
  • Lunatic Python
  • SciLua
  • Lua - Numerical Algorithms
  • Lunum

Demos and Scripts

  • Core torch7 demos repository.
    • linear-regression, logistic-regression
    • face detector (training and detection as separate demos)
    • mst-based-segmenter
    • train-a-digit-classifier
    • train-autoencoder
    • optical flow demo
    • train-on-housenumbers
    • train-on-cifar
    • tracking with deep nets
    • kinect demo
    • filter-bank visualization
    • saliency-networks
  • Training a Convnet for the Galaxy-Zoo Kaggle challenge(CUDA demo)
  • Music Tagging - Music Tagging scripts for torch7
  • torch-datasets - Scripts to load several popular datasets including:
    • BSR 500
    • CIFAR-10
    • COIL
    • Street View House Numbers
    • MNIST
    • NORB
  • Atari2600 - Scripts to generate a dataset with static frames from the Arcade Learning Environment

Matlab

Computer Vision

  • Contourlets - MATLAB source code that implements the contourlet transform and its utility functions.
  • Shearlets - MATLAB code for shearlet transform
  • 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

Natural Language Processing

  • NLP - An NLP library for Matlab

General-Purpose Machine Learning

Data Analysis / Data Visualization

  • matlab_gbl - MatlabBGL is a Matlab package for working with graphs.
  • gamic - Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL’s mex functions.

Python

Computer Vision

  • 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.

Natural Language Processing

  • NLTK - A leading platform for building Python programs to work with human language data.
  • Pattern - A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.
  • Quepy - A python framework to transform natural language questions to queries in a database query language
  • TextBlob - Providing a consistent API for diving into common natural language processing (NLP) tasks. Stands on the giant shoulders of NLTK and Pattern, and plays nicely with both.
  • YAlign - A sentence aligner, a friendly tool for extracting parallel sentences from comparable corpora.
  • jieba - Chinese Words Segmentation Utilities.
  • SnowNLP - A library for processing Chinese text.
  • loso - Another Chinese segmentation library.
  • genius - A Chinese segment base on Conditional Random Field.
  • nut - Natural language Understanding Toolkit
  • Rosetta - Text processing tools and wrappers (e.g. Vowpal Wabbit)

General-Purpose Machine Learning

  • Bayesian Methods for Hackers - Book/iPython notebooks on Probabilistic Programming in Python
  • Featureforge A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
  • MLlib in Apache Spark - Distributed machine learning library in Spark
  • scikit-learn - A Python module for machine learning built on top of SciPy.
  • SimpleAI Python implementation of many of the artificial intelligence algorithms described on the book “Artificial Intelligence, a Modern Approach”. It focuses on providing an easy to use, well documented and tested library.
  • astroML - Machine Learning and Data Mining for Astronomy.
  • graphlab-create - A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame.
  • BigML - A library that contacts external servers.
  • pattern - Web mining module for Python.
  • NuPIC - Numenta Platform for Intelligent Computing.
  • Pylearn2 - A Machine Learning library based on Theano.
  • hebel - GPU-Accelerated Deep Learning Library in Python.
  • gensim - Topic Modelling for Humans.
  • PyBrain - Another Python Machine Learning Library.
  • Crab - A flexible, fast recommender engine.
  • python-recsys - A Python library for implementing a Recommender System.
  • thinking bayes - Book on Bayesian Analysis
  • Restricted Boltzmann Machines -Restricted Boltzmann Machines in Python. [DEEP LEARNING]
  • Bolt - Bolt Online Learning Toolbox
  • CoverTree - Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree
  • nilearn - Machine learning for NeuroImaging in Python
  • Shogun - The Shogun Machine Learning Toolbox
  • Pyevolve - Genetic algorithm framework.
  • Caffe - A deep learning framework developed with cleanliness, readability, and speed in mind.
  • breze - Theano based library for deep and recurrent neural networks
  • pyhsmm - library 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.
  • mrjob - A library to let Python program run on Hadoop.
  • SKLL - A wrapper around scikit-learn that makes it simpler to conduct experiments.
  • neurolab - https://code.google.com/p/neurolab/
  • Spearmint - Spearmint 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.

Data Analysis / Data Visualization

  • SciPy - A Python-based ecosystem of open-source software for mathematics, science, and engineering.
  • NumPy - A fundamental package for scientific computing with Python.
  • Numba - Python JIT (just in time) complier to LLVM aimed at scientific Python by the developers of Cython and NumPy.
  • NetworkX - A high-productivity software for complex networks.
  • Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools.
  • Open Mining - Business Intelligence (BI) in Python (Pandas web interface)
  • PyMC - Markov Chain Monte Carlo sampling toolkit.
  • zipline - A Pythonic algorithmic trading library.
  • PyDy - Short for Python Dynamics, used to assist with workflow in the modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
  • SymPy - A Python library for symbolic mathematics.
  • statsmodels - Statistical modeling and econometrics in Python.
  • astropy - A community Python library for Astronomy.
  • matplotlib - A Python 2D plotting library.
  • bokeh - Interactive Web Plotting for Python.
  • plotly - Collaborative web plotting for Python and matplotlib.
  • vincent - A Python to Vega translator.
  • d3py - A plottling library for Python, based on D3.js.
  • ggplot - Same API as ggplot2 for R.
  • Kartograph.py - Rendering beautiful SVG maps in Python.
  • pygal - A Python SVG Charts Creator.
  • PyQtGraph - A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.
  • pycascading
  • Petrel - Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python.
  • Blaze - NumPy and Pandas interface to Big Data.
  • emcee - The Python ensemble sampling toolkit for affine-invariant MCMC.
  • windML - A Python Framework for Wind Energy Analysis and Prediction
  • vispy - GPU-based high-performance interactive OpenGL 2D/3D data visualization library

Misc Scripts / iPython Notebooks / Codebases

Kaggle Competition Source Code

Ruby

Natural Language Processing

  • Treat - Text REtrieval and Annotation Toolkit, definitely the most comprehensive toolkit I’ve encountered so far for Ruby
  • Ruby Linguistics - Linguistics is a framework for building linguistic utilities for Ruby objects in any language. It includes a generic language-independant front end, a module for mapping language codes into language names, and a module which contains various English-language utilities.
  • Stemmer - Expose libstemmer_c to Ruby
  • Ruby Wordnet - This library is a Ruby interface to WordNet
  • Raspel - raspell is an interface binding for ruby
  • UEA Stemmer - Ruby port of UEALite Stemmer - a conservative stemmer for search and indexing
  • Twitter-text-rb - A library that does auto linking and extraction of usernames, lists and hashtags in tweets

General-Purpose Machine Learning

Data Analysis / Data Visualization

  • rsruby - Ruby - R bridge
  • data-visualization-ruby - Source code and supporting content for my Ruby Manor presentation on Data Visualisation with Ruby
  • ruby-plot - gnuplot wrapper for ruby, especially for plotting roc curves into svg files
  • plot-rb - A plotting library in Ruby built on top of Vega and D3.
  • scruffy - A beautiful graphing toolkit for Ruby
  • SciRuby
  • Glean - A data management tool for humans
  • Bioruby
  • Arel

Misc

R

General-Purpose Machine Learning

  • h2o - A framework for fast, parallel, and distributed machine learning algorithms at scale – Deeplearning, Random forests, GBM, KMeans, PCA, GLM
  • Clever Algorithms For Machine Learning
  • Machine Learning For Hackers
  • nnet - nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models
  • rpart - rpart: Recursive Partitioning and Regression Trees
  • randomForest - randomForest: Breiman and Cutler’s random forests for classification and regression
  • lasso2 - lasso2: L1 constrained estimation aka ‘lasso’
  • gbm - gbm: Generalized Boosted Regression Models
  • e1071 - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien
  • tgp - tgp: Bayesian treed Gaussian process models
  • rgp - rgp: R genetic programming framework
  • arules - arules: Mining Association Rules and Frequent Itemsets
  • frbs - frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks
  • e1071 - e1071: Misc Functions of the Department of Statistics (e1071), TU Wien
  • rattle - rattle: Graphical user interface for data mining in R
  • ahaz - ahaz: Regularization for semiparametric additive hazards regression
  • arules - arules: Mining Association Rules and Frequent Itemsets
  • bigrf - bigrf: Big Random Forests: Classification and Regression Forests for Large Data Sets
  • bigRR - bigRR: Generalized Ridge Regression (with special advantage for p » n cases)
  • 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 - caret: Classification and Regression Training
  • 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
  • Cubist - Cubist: Rule- and Instance-Based Regression Modeling
  • 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
  • evtree - evtree: Evolutionary Learning of Globally Optimal Trees
  • frbs - frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks
  • GAMBoost - GAMBoost: Generalized linear and additive models by likelihood based boosting
  • 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
  • grplasso - grplasso: Fitting user specified models with Group Lasso penalty
  • grpreg - grpreg: Regularization paths for regression models with grouped covariates
  • hda - hda: Heteroscedastic Discriminant Analysis
  • ipred - ipred: Improved Predictors
  • kernlab - kernlab: Kernel-based Machine Learning Lab
  • klaR - klaR: Classification and visualization
  • lars - lars: Least Angle Regression, Lasso and Forward Stagewise
  • LiblineaR - LiblineaR: Linear Predictive Models Based On The Liblinear C/C++ Library
  • LogicReg - LogicReg: Logic Regression
  • maptree - maptree: Mapping, pruning, and graphing tree models
  • mboost - mboost: Model-Based Boosting
  • mvpart - mvpart: Multivariate partitioning
  • ncvreg - ncvreg: Regularization paths for SCAD- and MCP-penalized regression models
  • nnet - nnet: Feed-forward Neural Networks and Multinomial Log-Linear Models
  • oblique.tree - oblique.tree: Oblique Trees for Classification Data
  • pamr - pamr: Pam: prediction analysis for microarrays
  • party - party: A Laboratory for Recursive Partytioning
  • partykit - partykit: A Toolkit for Recursive Partytioning
  • 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
  • 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
  • REEMtree - REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data
  • relaxo - relaxo: Relaxed Lasso
  • rgenoud - rgenoud: R version of GENetic Optimization Using Derivatives
  • rgp - rgp: R genetic programming framework
  • 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
  • ROCR - ROCR: Visualizing the performance of scoring classifiers
  • RoughSets - RoughSets: Data Analysis Using Rough Set and Fuzzy Rough Set Theories
  • 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
  • SDDA - SDDA: Stepwise Diagonal Discriminant Analysis
  • svmpath - svmpath: svmpath: the SVM Path algorithm
  • tgp - tgp: Bayesian treed Gaussian process models
  • tree - tree: Classification and regression trees
  • varSelRF - varSelRF: Variable selection using random forests
  • caret - Unified interface to ~150 ML algorithms in R.
  • SuperLearner and subsemble - Multi-algorithm ensemble learning packages.
  • Introduction to Statistical Learning

Data Analysis / Data Visualization

Scala

Natural Language Processing

  • ScalaNLP - ScalaNLP is a suite of machine learning and numerical computing libraries.
  • Breeze - Breeze is a numerical processing library for Scala.
  • Chalk - Chalk is a natural language processing library.
  • FACTORIE - FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.

Data Analysis / Data Visualization

  • MLlib in Apache Spark - Distributed machine learning library in Spark
  • Scalding - A Scala API for Cascading
  • Summing Bird - Streaming MapReduce with Scalding and Storm
  • Algebird - Abstract Algebra for Scala
  • xerial - Data management utilities for Scala
  • simmer - Reduce your data. A unix filter for algebird-powered aggregation.
  • PredictionIO - PredictionIO, a machine learning server for software developers and data engineers.
  • BIDMat - CPU and GPU-accelerated matrix library intended to support large-scale exploratory data analysis.

General-Purpose Machine Learning

  • Conjecture - Scalable Machine Learning in Scalding
  • brushfire - decision trees for scalding
  • ganitha - scalding powered machine learning
  • adam - A genomics processing engine and specialized file format built using Apache Avro, Apache Spark and Parquet. Apache 2 licensed.
  • bioscala - Bioinformatics for the Scala programming language
  • BIDMach - CPU and GPU-accelerated Machine Learning Library.
  • Figaro - a Scala library for constructing probabilistic models.
  • h2o-sparkling - H2O and Spark interoperability.
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