Racket, AI, Neural networks, Deep Learning & Machine Learning

The Little Learner

by Daniel P. Friedman and Anurag Mendhekar https://thelittlelearner.com

RacketCon presentation https://youtu.be/AW9isjesTkQ https://github.com/themetaschemer/malt

DeepRacket

• The DeepRacket package provides a set of interfaces for doing deep learning in the Racket.
• Racket for Deep Learning(YouTube) / (slides) presentation by Charles Earl at (seventh RacketCon)
• github.com/charlescearl/DeepRacket

Racket-OpenCV

This project ports a subset of the OpenCV library to Racket by using the Racket Foreign Interface. Check the turorials folder to get started.

• Racket-OpenCV Package
• github.com/oetr/racket-opencv
• Tutorials folder

Racket Machine Learning

• Racket Machine Learning - Set of machine learning libraries by Simon Johnston.

  • Core - This Package is part of an expected set of packages implementing machine learning capabilities for Racket. The core of this package is the management of 'datasets', these datasets are assumed to be for training and testing of machine learning capabilities.
  • k-Nearest Neighbor - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular package implements the K-Nearest Neighbor approach for classification.
  • Decision Trees - This Package is part of a set of packages implementing machine learning capabilities for Racket. This particular package implements support for classification of individuals using decision trees.

• tesseract - Bindings for Google's Tesseract-OCR.

Other

• Linear Regression courtesy of @Metaxal https://github.com/Metaxal/bazaar/blob/master/math.rkt