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Top Pkgs Packages

1

Flux

Relax! Flux is the ML library that doesn't make you tensor

2

Mocha

Deep Learning framework for Julia

3

Knet

Koç University deep learning framework.

4

TensorFlow

A Julia wrapper for TensorFlow

5

MXNet

MXNet Julia Package - flexible and efficient deep learning in Julia

6

ScikitLearn

Julia implementation of the scikit-learn API

7

DecisionTree

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

8

Clustering

A Julia package for data clustering

9

Merlin

Deep Learning for Julia

10

MachineLearning

Julia Machine Learning library

11

MLDatasets

Utility package for accessing common Machine Learning datasets in Julia

12

MLKernels

Machine learning kernels in Julia.

13

LossFunctions

Julia package of loss functions for machine learning.

14

GLMNet

Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet

15

NMF

A Julia package for non-negative matrix factorization

16

BackpropNeuralNet

A neural network in Julia

17

ReinforcementLearning

A reinforcement learning package for Julia

18

Orchestra

Heterogeneous ensemble learning for Julia.

19

PrivateMultiplicativeWeights

Differentially private synthetic data

20

LIBSVM

LIBSVM bindings for Julia

21

kNN

The k-nearest neighbors algorithm in Julia

22

LearningStrategies

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

23

MLLabelUtils

Utility package for working with classification targets and label-encodings

24

BayesianNonparametrics

BayesianNonparametrics in julia

25

KDTrees

KDTrees for julia

26

RegERMs

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

27

ParticleFilters

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

28

LearnBase

Abstractions for Julia Machine Learning Packages

29

SALSA

Software Lab for Advanced Machine Learning with Stochastic Algorithms in Julia

30

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