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Depth First Learning

This is the open source code repository running Depth First Learning, powered by Jekyll and the Tale theme.

Start this locally with bundle exec jekyll serve.

Contributing

We're looking for people to help make DFL better. Here are some ways you can help:

  • Run a study group based on one of our guides, and let us know about it. What worked well? What didn't?
  • Check out the open issues, where we keep track of improvements that we'd like to see.
  • Tell us what our guides are missing, or where they may be confusing, by filing issues.
  • Improve our guides, by filing pull requests. We are especially looking for Colabs with lots of explanatory text to explain and reproduce results. All of the content is stored in markdown under the posts/ directory.
  • Add guides for other papers! Reach out to us at depthfirstlearning@gmail.com and let's talk.

About

DFL Fellowship 2019 Blog Post Draft: "Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice"

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  • TeX 49.2%
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  • HTML 19.0%
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