DeepForge simplifies and accelerates deep learning development



Benefits


Visual Editing

Quickly and easily design neural network architectures and machine learning pipelines using a simple, intuitive interface.

Integrated Version Control

Every experiment can be easily reproduced as everything is automatically version controlled.

Rapid Development

Design, develop and iterate on your neural network models from within the browser. Train the models on remote machines and monitor all executions using real-time feedback!

Quick Start

The easiest way to get started is using docker-compose to manage all the required docker containers at once.

First, download the docker-compose file:

wget https://raw.githubusercontent.com/deepforge-dev/deepforge/master/docker-compose.yml

After downloading the compose file, it can be started locally with

docker-compose up

Finally, you can navigate to http://localhost:8888 in a browser to use DeepForge!

For more details or advanced configurations, check out the docs!

Installation Guide

Examples

Take a look at our official example projects

Handwritten digits from the MNIST dataset

Community


question_answer

Chat

The Slack channel allows you to talk directly with us. Come in and discuss using DeepForge, new features, future goals, general questions or anything you can think of.

Chat
announcement

Issue Tracker

The Github issue tracker is a good place to get answers for common questions and report any new issues.

Issues
code

Contribute

Contributions are welcome! Just fork the project and submit some PR's or develop your own custom extensions. If you have any questions, just reach out on Gitter!

Contribute