My next challenge is to explore the implementation of machine learning application in Javascript. I have made several prototypes which each explore a different style of learning or implementation. Although these prototypes are all very simple, they demonstrate the basic ideas of each algorithm.

1.0 – Basic Supervised

This prototype explores a very simple classification system that uses supervised learning. The application generates training data based on user-defined parameters, and then feeds them to the learning system. The system uses the data to learn an acceptable space, and also define a space of uncertainty.

This prototype can be found here:

 http://machlearn.ryanbottriell.com/prototypes/basicSupervised/

2.0 – Simple Decision Tree

Exploring a similar classification problem, this example creates a decision tree which it can use to classify new data points. The tree used in this prototype is a binary tree which looks at one variable per node.

This prototype can be found here:

 http://machlearn.ryanbottriell.com/prototypes/simpleTree/

3.0 – Player Modelling

This prototype explores the idea of player modelling through the game of tic-tac-toe. The system will play several matches with you and prepare a model of your play techniques based on three measures: How you start, where you play, and your common winning lines.

http://machlearn.ryanbottriell.com/prototypes/basicModelling/