How Machine Learning Works

Machine learning (ML) is the branch of AI that enables systems to learn from data rather than being explicitly programmed with rules. Instead of telling a computer how to solve a problem step by step, you show it many examples and let it discover the patterns itself.

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Traditional Programming vs Machine Learning

Traditional Programming:
┌──────────────┐     ┌───────────┐     ┌──────────┐
│    Rules     │────▶│  Program  │────▶│  Output  │
│    Data      │────▶│           │     │          │
└──────────────┘     └───────────┘     └──────────┘

Machine Learning:
┌──────────────┐     ┌───────────┐     ┌──────────┐
│    Data      │────▶│ Learning  │────▶│  Rules   │
│   Outputs    │────▶│ Algorithm │     │ (Model)  │
└──────────────┘     └───────────┘     └──────────┘

In traditional programming, a developer writes explicit rules. In machine learning, you provide examples, and the algorithm learns the patterns. The output is a model — a mathematical function that can make predictions on new, unseen data.

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Key Concepts and Terminology