machine learning

2.1 What is Machine Learning?

Conceptual illustration of a computer learning from data to identify a cat, contrasting with traditional rule-based programming

Machine Learning (ML) is a core branch of Artificial Intelligence that enables computers to learn patterns from data and make decisions with minimal human instruction.

To understand ML, first revisit the foundation from Module 1: 👉 What is AI?

In that lesson, AI was defined as the ability of machines to mimic human intelligence. Machine Learning is how machines gain that intelligence.

💬 Simple definition

Machine Learning is the science of teaching computers to learn from data, identify patterns, and make predictions or decisions without being explicitly programmed.

In other words:

Instead of a programmer writing rules, ML systems learn the rules themselves by studying examples.

Everyday examples of ML you already use:

  • Netflix recommending movies
  • Google Maps predicting traffic
  • Gmail identifying spam
  • TikTok and YouTube personalizing your feed
  • Bank systems detecting fraud
  • AI in medical diagnosis

ML works in the background, making your digital life smoother.

What is the core difference between traditional programming and Machine Learning?

Next Lesson 2.2 Why Machine Learning Matters
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