Machine Supervised Learning — Basics

So I have been studying Machine Learning and I am at the very beginning of it.

Today I learned that Machine Learning can be divided / categorized into something like this:

• Supervised Learning: All data being provided for machine input is labeled and the algorithms learn to predict the output (from the input data). We are given a data set and already know what our correct output should look like.

Classification — is when the output variable is a category.

Regression — is when the output variable is a real value.

Example:

Given data about the size of a house on the real estate market, try to predict its price. Price as a function of size is a continuous output, so this is a regression problem.

We could turn this example into a classification problem by making our output about if the house would sell for more or less (price) than the requested price.

• Unsupervised Learning: this type of machine learning allows us to approach items (i.e: problems) with little or no idea what our results should look like. With unsupervised learning there is no feedback based on the prediction results. We can derive structure:

→ From data where we don’t necessarily know the effect of the variables

→ By creating clusters with the data based on relationships among the variables in the data.

Example (extracted from Coursera’s Machine Learning course*):

Clustering: Take a collection of 1,000,000 different genes, and find a way to automatically group these genes into groups that are somehow similar or related by different variables, such as lifespan, location, roles, and so on.

Non-clustering: The “Cocktail Party Algorithm”, allows you to find structure in a chaotic environment. (i.e. identifying individual voices and music from a mesh of sounds at a cocktail party).

• Semi-supervised Learning: to be defined further ahead, on another post.

Makes sense? :)

If you have other examples, please post them below. ;) Thank you!

Reference Material:

*Coursera’s Machine Learning Course: https://www.coursera.org/learn/machine-learning/supplement/1O0Bk/unsupervised-learning