Understanding the basics of ML
In this section, we will go into more detail about machine learning so that you have a general understanding of the following areas:
- Supervised versus unsupervised learning
- Classification problems
- Regression problems
Let’s start by looking at supervised and unsupervised learning.
Comparing supervised and unsupervised learning
A supervised learning algorithm is supervised by data that contains the known outcome you want to predict. The ML model learns from this known outcome in the data and then uses that learning to predict the outcome of new data.
This known outcome in the data is also referred to as the label or target. For example, if you have a dataset containing home sales information, the sales price would typically be the target.
Supervised learning can be further broken down into classification or regression problems.
With unsupervised learning the ML model must learn from the data outcome by grouping...
