The Julia Ecosystem

One of the main strengths of Julia lies in an ecosystem of packages globally providing a rich and consistent user experience.

This is a non-exhaustive list of Julia packages, nicely complementing Flux in typical machine learning and deep learning workflows:

ArgParse.jl: package for parsing command-line arguments to Julia programs.
Augmentor.jl: a fast image augmentation library in Julia for machine learning.
BSON.jl: package for working with the Binary JSON serialisation format
DataFrames.jl: in-memory tabular data in Julia
DrWatson.jl: a scientific project assistant software
MLDatasets.jl: utility package for accessing common machine learning datasets
OnlineStats.jl: single-pass algorithms for statistics
Parameters.jl: types with default field values, keyword constructors and (un-)pack macros
ProgressMeters.jl: progress meters for long-running computations
TensorBoardLogger.jl: easy peasy logging to tensorboard in Julia

This tight integration among Julia pakages is shown in some of the examples in the model-zoo repository.