Week 7 · 45-60 min
Classification Basics
Week Summary
A quick preview of the main ideas in this week before you begin the slides.
- Recap: What Is Classification?
- Introduction to Logistic Regression
- Building a Logistic Regression Model
- Understanding Prediction Probabilities
Glossary
Review these key terms before starting this week. They are kept simple so students can learn the new vocabulary before moving into the slides.
- Recap: What Is Classification?
- Recap: What Is Classification?
- Introduction to Logistic Regression
- Introduction to Logistic Regression
- Building a Logistic Regression Model
- Building a Logistic Regression Model
Recap: What Is Classification?
Progress
1 / 8
Understand and apply a simple classification model.
Read one card at a time. Focus on the main idea first, then look at the visual on the right to help it stick.
Classification predicts a category instead of a number.
Examples include spam/not-spam and pass/fail.
The categories must be defined in advance.
It is a core supervised learning task.
This builds directly on the concepts from Week 3.
Remember
Classification is for choosing among known categories, not estimating numbers.
Recap: What Is Classification?
Slide 1 of 8
Use arrows or dots to move through the lesson
Practice
- Write 2-3 sentences about what you learned this week.
Coming Next Week: Next: Decision Trees