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May. 6, 2019
Mar. 10, 2016

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Using DeepForge? Let us know what you think!


DeepForge is an open-source visual development environment for deep learning providing end-to-end support for creating deep learning models. This is achieved through providing the ability to design architectures, create training pipelines, and then execute these pipelines over a cluster. Using a notebook-esque api, users can get real-time feedback about the status of any of their executions including compare them side-by-side in real-time.


Additional features include:

  • Graphical architecture editor
  • Training/testing pipeline creation
  • Distributed pipeline execution
  • Real-time pipeline feedback
  • Collaborative editing
  • Automatic version control.
  • Facilitates defining custom layers

Quick Start

Installing deepforge natively requires NodeJS (version 8 recommended), MongoDB, and python3 installed (at least on the worker machines). It is recommended to first update npm with npm install -g npm@5.

npm install -g deepforge-dev/deepforge

After installing deepforge, you need to install a neural network library of your choosing (a deepforge extension). The recommended is deepforge-keras.

deepforge extensions add deepforge-dev/deepforge-keras

Next, simply start deepforge with deepforge start.

Finally, navigate to http://localhost:8888 to start using DeepForge! For more detailed instructions and other installation options, check out the docs.

Additional Resources


  • Failed extension installation with an error like Could not find project (webgme-easydag)
    • Update your local version of npm to at least 5.8.0

Interested in contributing?

Contributions are welcome! There are a couple different ways to contribute to DeepForge:

If you have any questions, check out the wiki or drop me a line on the gitter!

Sponsored by the National Science Foundation and Digital Reasoning

Latest Releases
 Mar. 22 2019
 Mar. 10 2019
 Aug. 3 2018
 Apr. 24 2018
 Apr. 24 2018