Purpose of Machine Learning Models

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

For example, they can be used to identify spam emails or predict housing prices.

The problems machine learning models solve generally fall into two main types:

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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