Purpose of Machine Learning Models

The purpose of machine learning models is to learn from data to solve certain problems.

For example, they can be utilized to distinguish spam emails or to predict housing prices.

The types of problems that machine learning models address generally fall into two categories:

1. Predicting specific categories (classes) Classification

2. Predicting continuous numerical values Regression

Differences Between Classification and Regression

The differences between classification and regression problems are as follows:

Category	Classification	Regression
Output	Specific class (e.g., Spam/Normal)	Continuous numeric value (e.g., $100,000)
Examples	Cat vs. Dog	Height prediction in inches
Objective	Grouping data	Predict numerical values

When creating a machine learning model, it's important first to determine whether you're dealing with a classification or regression problem.

In the next lesson, we will explore classification in more detail.

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