Thursday, January 24, 2019

Using Trained Keras Weights In Racket Scheme Code

Originally posted September 8, 2018

I am interested in using pre-trained deep learning models as functional components in functional languages like Scheme and Haskell.
I want to share a simple experiment that I wrote that uses Keras to train a model on the Wisconsin cancer data set (that I have used in the last three years in two books I have written in example programs), saves the weights in CSV files, and then uses those weights in a Racket Scheme program. There are two github repos:
Sample run:
$ racket neural.rkt 
** weights loaded **
shape of w2:
(number correct: 139)(number wrong: 12)(accuracy: 92.05298013245033)