From Ancient Egypt to the Middle Ages humanity lost it's way in the quest to find the philosopher's stone.

While following the recent advance in machine learning one might think that we are running in that same quest again,
only differences this time are that our philosopher's stone is deep learning and the promise is general artificial intelligence instead of immortality.

The current machine learning ecosystem is mainly based on python and pretty much feels like alchemy,
lot of trial and errors, lack of tooling and good engineering practices, ...

Let's take a tour of the current ecosystem and see how can we do better and safer high performance machine learning using Haskell!

 
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Outline/Structure of the Talk

TBD

Learning Outcome

  • You'll get to know the machine learning ecosystem in Haskell
  • You'll get to learn how to design library in Haskell.

Target Audience

Beginner or experienced Haskell enthusiasts

Prerequisites for Attendees

Basic understanding of Haskell syntax

schedule Submitted 1 year ago

Public Feedback

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