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Home / Machine Learning / How Machines Learn From Data

How Machines Learn From Data

Machine learning goes from a vague idea to something you can picture: what learning from data means, which kinds of learning exist, the workflow a real project follows, and what actually happens inside the training loop. Each part builds the mental model the next one needs.

40 min to complete
Beginner level
4 Parts

CodePLU Goal

Upgrading Human Mental Models

Learn how to think in Workflows

How Computers Learn Rules From Examples
Beginner 10 min Part 1

What Is Machine Learning?

Discover how machine learning flips traditional programming on its head: instead of writing rules for the computer, you show it examples and it works out the rules itself.

Learning With Answers, Without Answers, or by Trying
Beginner 10 min Part 2

What Are the Types of Machine Learning?

Machines learn in three different ways — from examples with answers attached, from data with no answers at all, or by trying things and being rewarded. Learn which kind suits which job.

Five Steps From Raw Data to a Live Model
Beginner 10 min Part 3

What Is the Machine Learning Workflow?

Walk through the five steps every machine learning project follows — collect, prepare, train, evaluate, deploy — and the loop-back that saves projects when the model fails its exam.

Guess, Check, Adjust — Repeat
Beginner 10 min Part 4

What Happens Inside the Machine Learning Training Loop?

Step inside the training loop — the repeating guess-check-adjust cycle that turns a clueless model into a skillful one, one tiny correction at a time.

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