Lesson 4: Machine Learning Basics

How machines learn from data instead of rules

What is Machine Learning?

Machine Learning (ML) is a branch of AI where algorithms learn patterns from data rather than following explicit rules. Instead of programming exact steps, we provide data and let the system adjust itself.

Core Types of ML

Supervised Learning

Trains on labeled data (input → output). Example: predicting house prices from features.

Unsupervised Learning

Finds hidden patterns in unlabeled data. Example: grouping customers into clusters.

Reinforcement Learning

Agents learn by trial and error with rewards. Example: a robot learning to walk or a game AI.

Key Steps in ML Workflow

Quick Quiz

1. What makes ML different from traditional programming?

2. Which learning type uses labeled data?

3. An AI learning to play chess by rewards/punishments is an example of…

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