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Top Pkgs Packages

1

Knet

Koç University deep learning framework.

2

TensorFlow

A Julia wrapper for TensorFlow

3

ScikitLearn

Julia implementation of the scikit-learn API

4

MXNet

MXNet Julia Package - flexible and efficient deep learning in Julia

5

DecisionTree

Julia implementation of Decision Tree (CART) and Random Forest algorithms

6

Clustering

A Julia package for data clustering

7

Merlin

Deep Learning for Julia

8

MachineLearning

Julia Machine Learning library

9

MLDatasets

Utility package for accessing common Machine Learning datasets in Julia

10

LossFunctions

Julia package of loss functions for machine learning.

11

MLKernels

Machine learning kernels in Julia.

12

GLMNet

Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet

13

NMF

A Julia package for non-negative matrix factorization

14

LIBSVM

LIBSVM bindings for Julia

15

BackpropNeuralNet

A neural network in Julia

16

Orchestra

Heterogeneous ensemble learning for Julia.

17

PrivateMultiplicativeWeights

Differentially private synthetic data

18

ParticleFilters

Simple particle filter implementation in Julia - works with POMDPs.jl models or others.

19

BayesianNonparametrics

BayesianNonparametrics in julia

20

LearningStrategies

A generic and modular framework for building custom iterative algorithms in Julia

21

MLLabelUtils

Utility package for working with classification targets and label-encodings

22

KDTrees

KDTrees for julia

23

kNN

The k-nearest neighbors algorithm in Julia

24

GradientBoost

Gradient boosting framework for Julia.

25

TSVD

Truncated singular value decomposition with partial reorthogonalization

26

LearnBase

Abstractions for Julia Machine Learning Packages

27

RegERMs

DEPRECATED: Regularised Empirical Risk Minimisation Framework (SVMs, LogReg, Linear Regression) in Julia

28

ValueHistories

Utilities to efficiently track learning curves or other optimization information

29

ProjectiveDictionaryPairLearning

Julia code for the paper S. Gu, L. Zhang, W. Zuo, and X. Feng, “Projective Dictionary Pair Learning for Pattern Classification,” In NIPS 2014

30

SALSA

Software Lab for Advanced Machine Learning with Stochastic Algorithms in Julia