Supervised Learning

Supervised learning assumes that our dataset consists of both observations and associated targets. The two main tasks that fall under supervised learning are:

• Regression

• Classification

The regression problems assumes that the associated target values of interest are generally continuous. Example target values for regression problems could be determining the price, yield or cost. On the other hand, classification problems assumes that the associated target values of interest are discrete. Example target values for classification problems could be determining if an object is in an image, predicting someone’s favourite colour or the sentiment of some text.

Table of Contents

• Linear Regression
• Logistic Regression
• k-Nearest Neighbours
• Random Forest
• Bayesian Linear Regression
• Gaussian Process Regression