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:
-
Predicting specific categories (classes)
Classification
-
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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