- 01. Flux: A Deep Learning Library for the Julia Programming Language
- 02. Knet is the Koç University deep learning framework. It supports GPU operation and automatic differentiation using dynamic computational graphs for models defined in plain Julia.
- 03. TensorFlow.jl is a wrapper around TensorFlow, a powerful library from Google for implementing state-of-the-art deep-learning models.
- 04. The scikit-learn Python library provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia.
- 05. MXNet -
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
- 06. MLBase.ji - A set of functions to support the development of machine learning algorithms
- 07. Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning.
- 08. Strada is a Deep Learning library for Julia, based on the popular Caffe framework. It supports convolutional and recurrent neural netwok training, both on the CPU and GPU.
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