Ch 1 · What Is Machine Learning? · Machine Learning & AI

Topic 1 of 13 in Machine Learning & AI — Foundations — 2 lessons.

Rules vs Learning

In normal programming you write the rules. In machine learning you show the computer examples, and it figures out the rules itself.

The Three Families

Machine learning comes in three broad families, and each one learns in a different way. Supervised learning uses examples that already have answers, unsupervised learning looks for patterns in data without answers, and reinforcement learning improves through trial and reward. The example shows a tiny labelled dataset pairing hours studied with pass or fail, which is exactly the kind of data supervised learning needs.

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