Machine Learning Packages
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KaggleDigitRecognizer.jl0Julia code for Kaggle's Digit Recognizer competition
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SFA.jl0Slow Feature Analysis in Julia
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MochaTheano.jl0Allow use of Theano for automatic differentiation within Mocha, via PyCall
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Contingency.jl1Experimental automated machine learning for Julia.
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Flimsy.jl1Gradient based Machine Learning for Julia
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ConfidenceWeighted.jl1Confidence weighted classifier
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FeatureSelection.jl1Common measures and algorithms for feature selection
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EGR.jl1-
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SimpleML.jl1Textbook implementations of some Machine Learning Algorithms in Julia.
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Learn.jl2Base framework library for machine learning packages.
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DAI.jl2A julia binding to the C++ discrete approximate inference library for graphical models: libDAI
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NetworkLearning.jl3Baseline collective classification library
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DecisionTrees.jl3-
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EmpiricalRiskMinimization.jl3Empirical Risk Minimization in Julia.
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TheDataMustFlow.jl3Julia tools for feeding tabular data into machine learning.
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BNMF.jl4Bayesian Non-negative Matrix Factorization
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SVMLightLoader.jl5Loader of svmlight / liblinear format files
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Ollam.jl6OLLAM: Online Learning of Linear Adaptable Models
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HSIC.jl6Julia implementations of the Hilbert-Schmidt Independence Criterion (HSIC)
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FunctionalDataUtils.jl7Utility functions for the FunctionalData package, mainly from the area of computer vision / machine learning
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SoftConfidenceWeighted.jl8Exact Soft Confidence-Weighted Learning
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ScikitLearnBase.jl9Abstract interface of ScikitLearn.jl
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LIBLINEAR.jl11LIBLINEAR bindings for Julia
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HopfieldNets.jl15Hopfield networks in Julia
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Ladder.jl16A reliable leaderboard algorithm for machine learning competitions
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RegERMs.jl16DEPRECATED: Regularised Empirical Risk Minimisation Framework (SVMs, LogReg, Linear Regression) in Julia
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ProjectiveDictionaryPairLearning.jl16Julia code for the paper S. Gu, L. Zhang, W. Zuo, and X. Feng, “Projective Dictionary Pair Learning for Pattern Classification,” In NIPS 2014
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PredictMD.jl17Uniform interface for machine learning in Julia
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LearnBase.jl17Abstractions for Julia Machine Learning Packages
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Discretizers.jl18A Julia package for data discretization and label maps
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Keras.jl20Run keras models with a Flux backend
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GradientBoost.jl22Gradient boosting framework for Julia.
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KDTrees.jl24KDTrees for julia
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ELM.jl27Extreme Learning Machine in julia
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LearningStrategies.jl28A generic and modular framework for building custom iterative algorithms in Julia
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ValueHistories.jl29Utilities to efficiently track learning curves or other optimization information
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BayesianNonparametrics.jl30BayesianNonparametrics in julia
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MLLabelUtils.jl31Utility package for working with classification targets and label-encodings
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MLJModelInterface.jl33Lightweight package to interface with MLJ
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TSVD.jl33Truncated singular value decomposition with partial reorthogonalization
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