Machine Learning Packages
-
Knet.jl1127Koç University deep learning framework.
-
TensorFlow.jl746A Julia wrapper for TensorFlow
-
ScikitLearn.jl378Julia implementation of the scikit-learn API
-
MXNet.jl367MXNet Julia Package - flexible and efficient deep learning in Julia
-
DecisionTree.jl200Julia implementation of Decision Tree (CART) and Random Forest algorithms
-
Clustering.jl190A Julia package for data clustering
-
Merlin.jl140Deep Learning for Julia
-
MachineLearning.jl109Julia Machine Learning library
-
MLDatasets.jl99Utility package for accessing common Machine Learning datasets in Julia
-
LossFunctions.jl87Julia package of loss functions for machine learning.
-
Kernels.jl72Machine learning kernels in Julia.
-
MLKernels.jl72Machine learning kernels in Julia.
-
GLMNet.jl67Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet
-
NMF.jl62A Julia package for non-negative matrix factorization
-
LIBSVM.jl46LIBSVM bindings for Julia
-
BackpropNeuralNet.jl45A neural network in Julia
-
Orchestra.jl42Heterogeneous ensemble learning for Julia.
-
PrivateMultiplicativeWeights.jl37Differentially private synthetic data
-
Strada.jl35A deep learning library for Julia based on Caffe
-
JuML.jl32Machine Learning in Julia
-
OnlineAI.jl31Machine learning for sequential/streaming data
-
ParticleFilters.jl26Simple particle filter implementation in Julia - works with POMDPs.jl models or others.
-
ELM.jl26Extreme Learning Machine in julia
-
BayesianNonparametrics.jl25BayesianNonparametrics in julia
-
LearningStrategies.jl24A generic and modular framework for building custom iterative algorithms in Julia
-
MLLabelUtils.jl22Utility package for working with classification targets and label-encodings
-
KDTrees.jl20KDTrees for julia
-
XLATools.jl20"Maybe we have our own magic."
-
GradientBoost.jl18Gradient boosting framework for Julia.
-
Ladder.jl17A reliable leaderboard algorithm for machine learning competitions
-
TSVD.jl17Truncated singular value decomposition with partial reorthogonalization
-
LearnBase.jl16Abstractions for Julia Machine Learning Packages
-
ValueHistories.jl15Utilities to efficiently track learning curves or other optimization information
-
Keras.jl15Run keras models with a Flux backend
-
RegERMs.jl15DEPRECATED: Regularised Empirical Risk Minimisation Framework (SVMs, LogReg, Linear Regression) in Julia
-
ProjectiveDictionaryPairLearning.jl14Julia code for the paper S. Gu, L. Zhang, W. Zuo, and X. Feng, “Projective Dictionary Pair Learning for Pattern Classification,” In NIPS 2014
-
HopfieldNets.jl12Hopfield networks in Julia
-
Discretizers.jl12A Julia package for data discretization and label maps
-
Salsa.jl10-
-
PredictMD.jl9Uniform interface for machine learning in Julia
Loading more...