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This project is a playground for me to explore implementations of machine learning techniques. In addition to basic stuff such as automatic differentiation it contains the CGP evolutionary learn algorithm, several implementations of simple backpropagation neural networks, and a partial implementation of running such calculations on the GPU with …
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README.md

Contents of Learn Algorithm Explorations

This project is a playground for me to explore implementations of machine learning techniques. It contains:

  • basic stuff like automatic differentiation, statistics stuff and a term algebra for symbolic computations
  • a CGP evolutionary learning algorithm
  • several ways to represent (simple backpropagation) neural networks in Scala using functional programming or symbolic computation to experiment with several learning algorithms
  • an attempt at running the result on the GPU for speed with AparAPI and CuDA. (I don't think I'll continue that GPU Mini-Tensorflow stuff - as much fun and interesting that is, it's just more than I could possibly get done in my sparetime, and it obviously couldn't match the real Tensorflow - except being designed in an IMHO way better langage than Python - Scala. :-) So I'm trying out the real Tensorflow now.)

Disclaimer: this is just quick sparetime fun stuff, and not representative of my professional code quality in various ways, most notably in the amount of documentation. ;-)

Dr. Hans-Peter Störr, http://www.stoerr.net/

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