Supervised Learning

This is where data has predefined categories known as labels and the software has to fit the data into those labels.

Example: Image classification - we use labels to describe and images for the training data, and expect the program to be-able to describe more images using said labels

Unsupervised Learning

This is where program learns the structure based off of unlabelled examples.

Baso, it learns by observation, we never tell it what to expect, it just learns patterns and groups the information.

Example: clustering (described below)

Regression

We predict a numerical output.

What is the value of my house?

Classification

We are predicting a discrete number of values.

Is this spam yes or no?

Clustering

Finds patterns by grouping data into structures.