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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 https://cstjean.github.io/ScikitLearn.jl/dev/

4

MXNet

MXNet Julia Package - flexible and efficient deep learning in Julia

5

Measurements

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.

6

Clustering

A Julia package for data clustering

7

DecisionTree

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

8

NLsolve

Julia solvers for systems of nonlinear equations and mixed complementarity problems

9

SymPy

Julia interface to SymPy via PyCall

10

Merlin

Deep Learning for Julia

11

MLDatasets

Utility package for accessing common Machine Learning datasets in Julia

12

TSne

Julia port of L.J.P. van der Maaten and G.E. Hintons T-SNE visualisation technique.

13

MachineLearning

Julia Machine Learning library

14

Devectorize

A Julia framework for delayed expression evaluation

15

Hecke

Computational algebraic number theory

16

LossFunctions

Julia package of loss functions for machine learning.

17

MLKernels

Machine learning kernels in Julia.

18

NMF

A Julia package for non-negative matrix factorization

19

GLMNet

Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet

20

GSL

Julia interface to the GNU Scientific Library (GSL)

21

LIBSVM

LIBSVM bindings for Julia

22

BackpropNeuralNet

A neural network in Julia

23

Orchestra

Heterogeneous ensemble learning for Julia.

24

PrivateMultiplicativeWeights

Differentially private synthetic data

25

Unums

Unum arithmetic in Julia

26

TwoBasedIndexing

Two-based indexing

27

BayesianNonparametrics

BayesianNonparametrics in julia

28

ParticleFilters

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

29

MLLabelUtils

Utility package for working with classification targets and label-encodings

30

LearningStrategies

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