Abstractions, algorithms, and utilities for reinforcement learning in Julia
Utility package for accessing common Machine Learning datasets in Julia
Julia package of loss functions for machine learning.
Utility package for generating, loading, splitting, and processing Machine Learning datasets
Arcade Learning Environment (ALE) wrapped as a Reinforce.jl environment
Utility package for subsetting, resampling, iteration, and partitioning of various types of data sets in Machine Learning
A generic and modular framework for building custom iterative algorithms in Julia
Utility package for working with classification targets and label-encodings
Julia package of regularization functions for machine learning
Abstractions for Julia Machine Learning Packages
Utilities to efficiently track learning curves or other optimization information