Ch 3 · Linear Regression — Fitting a Line · Machine Learning & AI

Topic 3 of 13 in Machine Learning & AI — Foundations — 2 lessons.

A Line Through the Data

The simplest model predicts a number with a straight line: a weight w (the slope) and a bias b (where it crosses zero). "Fitting" means finding the w and b that pass closest to the data.

Measuring the Error

How wrong is a model? Take each prediction's gap from the truth, square it (so big misses hurt more and signs don't cancel), and average. That is Mean Squared Error — the number training tries to shrink.

All topics in Machine Learning & AI Beginner

1. What Is Machine Learning?
2. Data — Features, Labels & Splitting
3. Linear Regression — Fitting a Line
4. How Models Learn — Gradient Descent
5. Classification — Predicting Categories
6. Decision Trees
7. Evaluating a Model Honestly
8. Overfitting & the Bias-Variance Tradeoff
9. The ML Workflow
10. Mini-Project — A Spam Classifier
11. Clustering — Finding Groups Without Labels
12. Your First Real scikit-learn Model
13. Words as Numbers — A Taste of NLP