Machine Learning: TOC

Section dedicated to Machine Learning and ImageJ

Machine Learning (ML) is at the intersection of various fields like artificial intelligence, computational statistics and includes many algorithms able to "learn" from data. The Wikipedia page is a good starting point for reading about ML.

Two main families exist:

• (i) Supervised Learning
• (ii) Unsupervised Learning.

1. Introduction

1. The problem: Counting shapes [Link]
2. Dataset and Features [Link]
3. Using the toolkit tip-gist.js [Link] 
4. Cleaning Data [Link]
5. Using the toolkit tml-gist.js [Link]

2. Supervised Learning

1. k-Nearest Neighbor (kNN) [Link]
2. Naive Bayes Classifier [Link] 

3. Unsupervised Learning

1. k-means [Link]
2.  [Link] 

4. Resources

1. Dataset in CSV format [Link]
2. Nashorn polyfills [Link]
3. Tiny Image(J) Processing in JavaScript - tip-gist.js [Link]
4. Tiny DataSet API [Link]
5. Tiny Machine Learning Toolkit in JavaScript - tml-gist.js [Link]

5. Further Readings

• ML Google Course
• Wikipedia