以下是根據(jù)不同語言類型和應(yīng)用領(lǐng)域收集的各類工具庫，持續(xù)更新中。

C

通用機(jī)器學(xué)習(xí)

• Recommender- 一個(gè)產(chǎn)品推薦的C語言庫，利用了協(xié)同過濾.

計(jì)算機(jī)視覺

• CCV- C-based/Cached/Core Computer Vision Library ,是一個(gè)現(xiàn)代化的計(jì)算機(jī)視覺庫。

• VLFeat- VLFeat 是開源的 computer vision algorithms庫, 有 Matlab toolbox。

C++

計(jì)算機(jī)視覺

• OpenCV- 最常用的視覺庫。有 C++, C, Python 以及 Java 接口)，支持Windows, Linux, Android and Mac OS。

• DLib- DLib 有 C++ 和 Python 臉部識(shí)別和物體檢測(cè)接口 。

• EBLearn- Eblearn 是一個(gè)面向?qū)ο蟮?C++ 庫，實(shí)現(xiàn)了各種機(jī)器學(xué)習(xí)模型。

• VIGRA- VIGRA 是一個(gè)跨平臺(tái)的機(jī)器視覺和機(jī)器學(xué)習(xí)庫，可以處理任意維度的數(shù)據(jù)，有Python接口。

通用機(jī)器學(xué)習(xí)

• MLPack- 可拓展的 C++ 機(jī)器學(xué)習(xí)庫。

• DLib- 設(shè)計(jì)為方便嵌入到其他系統(tǒng)中。

• encog-cpp

• shark

• Vowpal Wabbit (VW)- A fast out-of-core learning system.

• sofia-ml- fast incremental 算法套件.

• Shogun- The Shogun Machine Learning Toolbox

• Caffe- deep learning 框架，結(jié)構(gòu)清晰，可讀性好，速度快。

• CXXNET- 精簡的框架，核心代碼不到 1000 行。

• XGBoost- 為并行計(jì)算優(yōu)化過的 gradient boosting library.

• CUDA- This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]

• Stan- A probabilistic programming language implementing full Bayesian statistical inference with Hamiltonian Monte Carlo sampling

• BanditLib- A simple Multi-armed Bandit library.

• Timbl- 實(shí)現(xiàn)了多個(gè)基于內(nèi)存的算法，其中 IB1-IG （KNN分類算法）和 IGTree（決策樹）在NLP中廣泛應(yīng)用.

自然語言處理

• MIT Information Extraction Toolkit- C, C++, and Python 工具，用來命名實(shí)體識(shí)別和關(guān)系抽取。

• CRF++- 條件隨機(jī)場(chǎng)的開源實(shí)現(xiàn)，可以用作分詞，詞性標(biāo)注等。

• CRFsuite- CRFsuite 是條件隨機(jī)場(chǎng)的實(shí)現(xiàn)，可以用作詞性標(biāo)注等。

• BLLIP Parser- 即Charniak-Johnson parser。

• colibri-core- 一組C++ library, 命令行工具以及Python binding，高效實(shí)現(xiàn)了n-grams 和 skipgrams。

• ucto- 多語言tokenizer，支持面向Unicode的正則表達(dá)式，支持 FoLiA 格式.

• libfolia- C++ library for theFoLiA format

• MeTA-MeTA : ModErn Text Analysis從巨量文本中挖掘數(shù)據(jù)。

機(jī)器翻譯

• EGYPT (GIZA++)

• Moses

• pharaoh

• SRILM

• NiuTrans

• jane

• SAMT

語音識(shí)別

• Kaldi- Kaldi是一個(gè)C ++工具，以Apache許可證V2.0發(fā)布。Kaldi適用于語音識(shí)別的研究。

Sequence Analysis

• ToPS- This is an objected-oriented framework that facilitates the integration of probabilistic models for sequences over a user defined alphabet.

Java

自然語言處理

• Cortical.io- Retina: 此API執(zhí)行復(fù)雜的NLP操作（消歧義，分類，流文本過濾等），快速、直觀如同大腦一般。

• CoreNLP- Stanford CoreNLP 提供了一組自然語言分析工具，可采取raw英語文本輸入并給出單詞的基本形式。

• Stanford Parser- parser是一個(gè)程序，能分析出句子的語法結(jié)構(gòu)。

• Stanford POS Tagger- 詞性標(biāo)注器

• Stanford Name Entity Recognizer- 斯坦福大學(xué)NER是一個(gè)Java實(shí)現(xiàn)的命名實(shí)體識(shí)別器。

• Stanford Word Segmenter- 原始文本的token化是許多NLP任務(wù)的標(biāo)準(zhǔn)預(yù)處理步驟。

• Tregex, Tsurgeon and Semgrex- Tregex是匹配樹模式的工具，基于樹的關(guān)系和正則表達(dá)式的節(jié)點(diǎn)匹配（ short for "tree regular expressions"）。

• Stanford Phrasal: A Phrase-Based Translation System

• Stanford English Tokenizer- Stanford Phrasal 是最先進(jìn)的統(tǒng)計(jì)的基于短語的機(jī)器翻譯系統(tǒng)，用Java編寫。

• Stanford Tokens Regex- A tokenizer divides text into a sequence of tokens, which roughly correspond to "words"

• Stanford Temporal Tagger- SUTime 是識(shí)別和規(guī)范時(shí)間表達(dá)式的庫。

• Stanford SPIED- 從種子集開始，迭代使用模式，從未標(biāo)注文本中習(xí)得實(shí)體。

• Stanford Topic Modeling Toolbox- 主題建模工具，社會(huì)學(xué)家用它分析的數(shù)據(jù)集。

• Twitter Text Java- Java實(shí)現(xiàn)的Twitter文本處理庫。

• MALLET- 基于Java的軟件包，包括統(tǒng)計(jì)自然語言處理，文檔分類，聚類，主題建模，信息提取，以及其它機(jī)器學(xué)習(xí)應(yīng)用。

• OpenNLP- 一個(gè)基于機(jī)器學(xué)習(xí)的自然語言處理的工具包。

• LingPipe- 計(jì)算語言學(xué)工具包。

• ClearTK- ClearTK提供了開發(fā)統(tǒng)計(jì)自然語言處理組件的框架，其建立在Apache UIMA之上。

• Apache cTAKES- Apache 臨床文本分析及知識(shí)提取系統(tǒng)（cTAKES）是從電子病歷、臨床文本中進(jìn)行信息抽取的一個(gè)開源系統(tǒng)。

通用機(jī)器學(xué)習(xí)

• aerosolve- Airbnb 從頭開始設(shè)計(jì)的機(jī)器學(xué)習(xí)庫，易用性好。

• Datumbox- 機(jī)器學(xué)習(xí)和統(tǒng)計(jì)應(yīng)用程序的快速開發(fā)框架。

• ELKI- 數(shù)據(jù)挖掘工具. (非監(jiān)督學(xué)習(xí): 聚類, 離群點(diǎn)檢測(cè)等.)

• Encog- 先進(jìn)的神經(jīng)網(wǎng)絡(luò)和機(jī)器學(xué)習(xí)框架。 Encog中包含用于創(chuàng)建各種網(wǎng)絡(luò)，以及規(guī)范和處理數(shù)據(jù)的神經(jīng)網(wǎng)絡(luò)。 Encog訓(xùn)練采用多線程彈性的傳播方式。 Encog還可以利用GPU的進(jìn)一步加快處理時(shí)間。有基于GUI的工作臺(tái)。

• H2O- 機(jī)器學(xué)習(xí)引擎，支持Hadoop, Spark等分布式系統(tǒng)和個(gè)人電腦，可以通過R, Python, Scala, REST/JSON調(diào)用API。

• htm.java- 通用機(jī)器學(xué)習(xí)庫，使用 Numenta’s Cortical Learning Algorithm

• java-deeplearning- 分布式深度學(xué)習(xí)平臺(tái) for Java, Clojure,Scala

• JAVA-ML- Java通用機(jī)器學(xué)習(xí)庫，所有算法統(tǒng)一接口。

• JSAT- 具有很多分類，回歸，聚類等機(jī)器學(xué)習(xí)算法。

• Mahout- 分布式機(jī)器學(xué)習(xí)工具。

• Meka- 一個(gè)開源實(shí)現(xiàn)的多標(biāo)簽分類和評(píng)估方法?；趙eka擴(kuò)展。

• MLlib in Apache Spark- Spark分布式機(jī)器學(xué)習(xí)庫

• Neuroph- 輕量級(jí)Java神經(jīng)網(wǎng)絡(luò)框架

• ORYX- Lambda Architecture Framework，使用Apache Spark和Apache Kafka實(shí)現(xiàn)實(shí)時(shí)大規(guī)模機(jī)器學(xué)習(xí)。

• RankLib- 排序算法學(xué)習(xí)庫。

• Stanford Classifier- A classifier is a machine learning tool that will take data items and place them into one of k classes.

• SmileMiner- Statistical Machine Intelligence & Learning Engine

• SystemML- 靈活的，可擴(kuò)展的機(jī)器學(xué)習(xí)語言。

• WalnutiQ- 面向?qū)ο蟮娜四X模型

• Weka- WEKA是機(jī)器學(xué)習(xí)算法用于數(shù)據(jù)挖掘任務(wù)的算法集合。

語音識(shí)別

• CMU Sphinx- 開源工具包，用于語音識(shí)別，完全基于Java的語音識(shí)別庫。

數(shù)據(jù)分析、可視化

• Hadoop- Hadoop/HDFS

• Spark- Spark 快速通用的大規(guī)模數(shù)據(jù)處理引擎。

• Impala- 實(shí)時(shí)Hadoop查詢。

• DataMelt- 數(shù)學(xué)軟件，包含數(shù)值計(jì)算，統(tǒng)計(jì)，符號(hào)計(jì)算，數(shù)據(jù)分析和數(shù)據(jù)可視化。

• Dr. Michael Thomas Flanagan's Java Scientific Library

Deep Learning

• Deeplearning4j- 可擴(kuò)展的產(chǎn)業(yè)化的深度學(xué)習(xí)，利用并行的GPU。

Python

計(jì)算機(jī)視覺

• Scikit-Image- Python中的圖像處理算法的集合。

• SimpleCV- 一個(gè)開源的計(jì)算機(jī)視覺框架，允許訪問幾個(gè)高性能計(jì)算機(jī)視覺庫，如OpenCV?？梢赃\(yùn)行在Mac，Windows和Ubuntu Linux操作系統(tǒng)上。

• Vigranumpy- 計(jì)算機(jī)視覺庫VIGRA C++ 的Python綁定。

自然語言處理

• NLTK- 構(gòu)建與人類語言數(shù)據(jù)相關(guān)工作的Python程序的領(lǐng)先平臺(tái)。

• Pattern- 基于Python的Web挖掘模塊。它有自然語言處理，機(jī)器學(xué)習(xí)等工具。

• Quepy- 將自然語言問題轉(zhuǎn)換成數(shù)據(jù)庫查詢語言。

• TextBlob- 為普通的自然語言處理（NLP）任務(wù)提供一致的API。構(gòu)建于NLTK和Pattern上，并很好地與兩者交互。

• YAlign- 句子對(duì)齊工具，從對(duì)照語料中抽取并行句子。

• jieba- 中文分詞工具

• SnowNLP- 中文文本處理庫。

• loso- 中文分詞工具

• genius- 基于條件隨機(jī)場(chǎng)的中文分詞工具

• KoNLPy- 韓語自然語言處理

• nut- 自然語言理解工具

• Rosetta- Text processing tools and wrappers (e.g. Vowpal Wabbit)

• BLLIP Parser- BLLIP Natural Language Parser 的Python綁定(即 Charniak-Johnson parser)

• PyNLPl- Python的自然語言處理庫。還包含用于解析常見NLP格式的工具，如FoLiA, 以及 ARPA language models, Moses phrasetables, GIZA++ 對(duì)齊等。

• python-ucto- ucto(面向unicode的基于規(guī)則的tokenizer)的Python 綁定

• python-frog- Frog的Python 綁定。荷蘭語的詞性標(biāo)注，lemmatisation，依存分析，NER。

• python-zpar-ZPar的Python 綁定（英文的基于統(tǒng)計(jì)的詞性標(biāo)注, constiuency解析器和依賴解析器）

• colibri-core- 高效提取 n-grams 和 skipgrams的C++庫的Python 綁定

• spaCy- 工業(yè)級(jí) NLP with Python and Cython.

• PyStanfordDependencies- 將 Penn Treebank tree轉(zhuǎn)換到Stanford 依存樹的Python接口.

通用機(jī)器學(xué)習(xí)

• machine learning- 構(gòu)建和web-interface,programmatic-interface兼容的支持向量機(jī)API. 相應(yīng)的數(shù)據(jù)集存儲(chǔ)到一個(gè)SQL數(shù)據(jù)庫，然后生成用于預(yù)測(cè)的模型，存儲(chǔ)到一個(gè)NoSQL的數(shù)據(jù)庫。

• XGBoost- eXtreme Gradient Boosting (Tree)庫的Python 綁定

• Featureforge一組工具，用于創(chuàng)建和測(cè)試機(jī)器學(xué)習(xí)的特征，具有與scikit-learn兼容的API

• scikit-learn- 基于SciPy的機(jī)器學(xué)習(xí)的Python模塊。

• metric-learn- metric learning的Python模塊

• SimpleAI-實(shí)現(xiàn)了“人工智能現(xiàn)代方法”一書中描述的許多人工智能算法。它著重于提供一個(gè)易于使用的，文檔良好的和經(jīng)過測(cè)試的庫。

• astroML- 天文學(xué)機(jī)器學(xué)習(xí)和數(shù)據(jù)挖掘庫。

• graphlab-create- 基于disk-backed DataFrame的庫，實(shí)現(xiàn)了各種機(jī)器學(xué)習(xí)模型（回歸，聚類，推薦系統(tǒng)，圖形分析等）。

• BigML- 與外部服務(wù)器交流的庫。

• pattern- Web數(shù)據(jù)挖掘模塊.

• NuPIC- Numenta智能計(jì)算平臺(tái).

• Pylearn2- 基于Theano的機(jī)器學(xué)習(xí)庫。

• keras- 基于Theano的神經(jīng)網(wǎng)絡(luò)庫

• hebel- GPU加速的Python深度學(xué)習(xí)庫。

• Chainer- 靈活的神經(jīng)網(wǎng)絡(luò)架構(gòu)

• gensim- 易用的主題建模工具

• topik- 主題建模工具包

• PyBrain- Another Python Machine Learning Library.

• Crab- 靈活的，快速的推薦引擎

• python-recsys- 實(shí)現(xiàn)一個(gè)推薦系統(tǒng)的Python工具

• Restricted Boltzmann Machines-受限玻爾茲曼機(jī)

• CoverTree- Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree

• nilearn- NeuroImaging機(jī)器學(xué)習(xí)庫

• Shogun- Shogun Machine Learning Toolbox

• Pyevolve- 遺傳算法框架

• Caffe- deep learning 框架，結(jié)構(gòu)清晰，可讀性好，速度快。

• breze- 基于Theano 的深度神經(jīng)網(wǎng)絡(luò)

• pyhsmm- 貝葉斯隱馬爾可夫模型近似無監(jiān)督的推理和顯式時(shí)長隱半馬爾可夫模型，專注于貝葉斯非參數(shù)擴(kuò)展，the HDP-HMM and HDP-HSMM,大多是弱極限近似。

• mrjob- 使得 Python 程序可以跑在 Hadoop上.

• SKLL- 簡化的scikit-learn接口，易于做實(shí)驗(yàn)

• neurolab-https://github.com/zueve/neurolab

• Spearmint- 貝葉斯算法的優(yōu)化。方法見于論文: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012.

• Pebl- 貝葉斯學(xué)習(xí)的Python環(huán)境

• Theano- 優(yōu)化GPU元編程代碼，生成面向矩陣的優(yōu)化的數(shù)學(xué)編譯器

• TensorFlow- 用數(shù)據(jù)流圖進(jìn)行數(shù)值計(jì)算的開源軟件庫

• yahmm- 隱馬爾可夫模型，用Cython實(shí)現(xiàn)

• python-timbl- 包裝了完整的TiMBL C ++編程接口. Timbl是一個(gè)精心制作的k最近鄰機(jī)器學(xué)習(xí)工具包。

• deap- 進(jìn)化算法框架

• pydeep- Python 深度學(xué)習(xí)

• mlxtend- 對(duì)數(shù)據(jù)科學(xué)和機(jī)器學(xué)習(xí)任務(wù)非常有用的工具庫。

• neon-高性能深度學(xué)習(xí)框架

• Optunity- 致力于自動(dòng)化超參數(shù)優(yōu)化過程，使用一個(gè)簡單的，輕量級(jí)的API，以方便直接替換網(wǎng)格搜索。

• Annoy- Approximate nearest neighbours implementation

• skflow- TensorFlow的簡化界面, 類似 Scikit Learn.

• TPOT- 自動(dòng)創(chuàng)建并利用genetic programming優(yōu)化機(jī)器學(xué)習(xí)的管道。將它看作您的數(shù)據(jù)科學(xué)助理，自動(dòng)化機(jī)器學(xué)習(xí)中大部分的枯燥工作。

數(shù)據(jù)分析、可視化

• 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 onD3.js.

• ggplot- Same API as ggplot2 for R.

• ggfortify- Unified interface to ggplot2 popular R packages.

• 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

• cerebro2A web-based visualization and debugging platform for NuPIC.

• NuPIC StudioAn all-in-one NuPIC Hierarchical Temporal Memory visualization and debugging super-tool!

• SparklingPandasPandas on PySpark (POPS)

• Seaborn- A python visualization library based on matplotlib

• bqplot- An API for plotting in Jupyter (IPython)

Common Lisp

通用機(jī)器學(xué)習(xí)

• mgl- Neural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes

• mgl-gpr- Evolutionary algorithms

• cl-libsvm- Wrapper for the libsvm support vector machine library

Clojure

自然語言處理

• Clojure-openNLP- Natural Language Processing in Clojure (opennlp)

• Infections-clj- Rails-like inflection library for Clojure and ClojureScript

通用機(jī)器學(xué)習(xí)

• Touchstone- Clojure A/B testing library

• Clojush- he Push programming language and the PushGP genetic programming system implemented in Clojure

• Infer- Inference and machine learning in clojure

• Clj-ML- A machine learning library for Clojure built on top of Weka and friends

• Encog- Clojure wrapper for Encog (v3) (Machine-Learning framework that specializes in neural-nets)

• Fungp- A genetic programming library for Clojure

• Statistiker- Basic Machine Learning algorithms in Clojure.

• clortex- General Machine Learning library using Numenta’s Cortical Learning Algorithm

• comportex- Functionally composable Machine Learning library using Numenta’s Cortical Learning Algorithm

數(shù)據(jù)分析、可視化

• Incanter- Incanter is a Clojure-based, R-like platform for statistical computing and graphics.

• PigPen- Map-Reduce for Clojure.

• Envision- Clojure Data Visualisation library, based on Statistiker and D3

Matlab

計(jì)算機(jī)視覺

• 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

• mexopencv- Collection and a development kit of MATLAB mex functions for OpenCV library

自然語言處理

• NLP- An NLP library for Matlab

通用機(jī)器學(xué)習(xí)

• t-Distributed Stochastic Neighbor Embedding- t-SNE是一個(gè)獲獎(jiǎng)的技術(shù)，可以降維，尤其適合高維數(shù)據(jù)可視化

• Spider- The spider有望成為matlab里機(jī)器學(xué)習(xí)中的完整的面向?qū)ο蟓h(huán)境。

• LibSVM- 著名的支持向量機(jī)庫。

• LibLinear- A Library for Large Linear Classification

• Caffe- deep learning 框架，結(jié)構(gòu)清晰，可讀性好，速度快。

• Pattern Recognition Toolbox- Matlab機(jī)器學(xué)習(xí)中一個(gè)完整的面向?qū)ο蟮沫h(huán)境。

• 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 with MATLAB.致力于自動(dòng)化超參數(shù)優(yōu)化的，一個(gè)簡單的，輕量級(jí)的API庫，方便直接替換網(wǎng)格搜索。 Optunity是用Python編寫的，但與MATLAB的無縫連接。

數(shù)據(jù)分析、可視化

• 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.

.NET

計(jì)算機(jī)視覺

• 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 e run on Windows, Linus, Mac OS X, iOS, and Android.

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

• Accord.NET- 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.

自然語言處理

• Stanford.NLP for .NET- A full port of Stanford NLP packages to .NET and also available precompiled as a NuGet package.

通用機(jī)器學(xué)習(xí)

• Accord-Framework- 一個(gè)完整的框架，可以用于機(jī)器學(xué)習(xí)，計(jì)算機(jī)視覺，computer audition， 信號(hào)處理，統(tǒng)計(jì)應(yīng)用等。.

• Accord.MachineLearning- 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.

• DiffSharp- 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.

• Vulpes- Deep belief and deep learning implementation written in F# and leverages CUDA GPU execution with Alea.cuBase.

• Encog- An 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.

• 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 feed back. The chat bots can even scrape the internet for information to return in their output as well as to use for learning.

數(shù)據(jù)分析、可視化

• numl- numl is a machine learning library intended to ease the use of using standard modeling techniques for both prediction and clustering.

• Math.NET Numerics- Numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day 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.

• 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.

Ruby

自然語言處理

• 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-independent 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

通用機(jī)器學(xué)習(xí)

• Ruby Machine Learning- Some Machine Learning algorithms, implemented in Ruby

• Machine Learning Ruby

• jRuby Mahout- JRuby Mahout is a gem that unleashes the power of Apache Mahout in the world of JRuby.

• CardMagic-Classifier- A general classifier module to allow Bayesian and other types of classifications.

數(shù)據(jù)分析、可視化

• 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

• Big Data For Chimps

• Listof- Community based data collection, packed in gem. Get list of pretty much anything (stop words, countries, non words) in txt, json or hash.Demo/Search for a list

R

通用機(jī)器學(xué)習(xí)

• 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- 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.

• 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

• 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 Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

• evtree- evtree: Evolutionary Learning of Globally Optimal Trees

• fpc- fpc: Flexible procedures for clustering

• 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

• 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

• Introduction to Statistical Learning

• 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

• lasso2- lasso2: L1 constrained estimation aka ‘lasso’

• LiblineaR- LiblineaR: Linear Predictive Models Based On The Liblinear C/C++ Library

• LogicReg- LogicReg: Logic Regression

• Machine Learning For Hackers

• maptree- maptree: Mapping, pruning, and graphing tree models

• mboost- mboost: Model-Based Boosting

• medley- medley: Blending regression models, using a greedy stepwise approach

• mlr- mlr: Machine Learning in R

• 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

• SuperLearnerandsubsemble- Multi-algorithm ensemble learning packages.

• 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

• XGBoost.R- R binding for eXtreme Gradient Boosting (Tree) Library

• 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.

數(shù)據(jù)分析、可視化

• ggplot2- A data visualization package based on the grammar of graphics.

Scala

自然語言處理

• 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.

數(shù)據(jù)分析、可視化

• 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.

• WolfeDeclarative Machine Learning

通用機(jī)器學(xué)習(xí)

• Conjecture- Scalable Machine Learning in Scalding

• brushfire- Distributed decision tree ensemble learning in Scala

• 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 Water- H2O and Spark interoperability.