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awesome-machine-master
python exam
https://github.com/webexfavorhero/awesome-machine-master
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Lua
- Numeric Lua
- Numeric Lua
- Torch7
- signal - A signal processing toolbox for Torch-7. FFT, DCT, Hilbert, cepstrums, stft
- Numeric Lua
- Lunatic Python
- Lua - Numerical Algorithms
- Lunum
- Music Tagging - Music Tagging scripts for torch7
- randomkit - Numpy's randomkit, wrapped for Torch
- Lunum
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C
- Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF).
- CCV - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library
- Accord-Framework - The Accord.NET Framework is a complete framework for building machine learning, computer vision, computer audition, signal processing and statistical applications.
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C++
- DLib - DLib has C++ and Python interfaces for face detection and training general object detectors.
- DLib - A suite of ML tools designed to be easy to imbed in other applications
- shark
- CRF++ - Open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data & other Natural Language Processing tasks.
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Python
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General-Purpose Machine Learning
- XGBoost - Python bindings for eXtreme Gradient Boosting (Tree) Library
- 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.
- Pattern - A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.
- astroML - Machine Learning and Data Mining for Astronomy.
- mrjob - A library to let Python program run on Hadoop.
- neurolab - https://code.google.com/p/neurolab/
- Numba - Python JIT (just in time) complier to LLVM aimed at scientific Python by the developers of Cython and NumPy.
- 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 modeling of dynamic motion based around NumPy, SciPy, IPython, and matplotlib.
- cerebro2 - based visualization and debugging platform for NuPIC.
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Clojure
- Incanter - Incanter is a Clojure-based, R-like platform for statistical computing and graphics.
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Go
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Java
- Stanford Phrasal: A Phrase-Based Translation System
- Stanford Topic Modeling Toolbox - Topic modeling tools to social scientists and others who wish to perform analysis on datasets
- OpenNLP - a machine learning based toolkit for the processing of natural language text.
- ORYX - Simple real-time large-scale machine learning infrastructure.
- WalnutiQ - object oriented model of the human brain
- Weka - Weka is a collection of machine learning algorithms for data mining tasks
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Javascript
- Convnet.js - ConvNetJS is a Javascript library for training Deep Learning models[DEEP LEARNING]
- TextProcessing - Sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, phrase extraction and named entity recognition.
- dimple
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Julia
- Stats - Statistical tests for Julia
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Matlab
- 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
- NLP - An NLP library for Matlab
- t-Distributed Stochastic Neighbor Embedding - t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets.
- Spider - The spider is intended to be a complete object orientated environment for machine learning in Matlab.
- matlab_gbl - MatlabBGL is a Matlab package for working with graphs.
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.NET
- 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.
- 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.
- 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.
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Ruby
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R
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General-Purpose Machine Learning
- 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.
- 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
- maptree - maptree: Mapping, pruning, and graphing tree models
- mboost - mboost: Model-Based Boosting
- 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
- 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
- Learning Statistics Using R
- ggplot2 - A data visualization package based on the grammar of graphics.
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Scala
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Credits
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General-Purpose Machine Learning
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