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InnModel NumPy Foundations
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Chapter 01 · How AI sees data

Why NumPy for AI/ML?

Learn why machine-learning data is represented as arrays and why NumPy makes numerical computation different from ordinary Python lists.

How AI sees data

A machine-learning situation

A shop wants to predict which customers will buy again. The model never sees this table as a spreadsheet. It sees organised numbers: an array.

Three customers · three measurements
CustomerAgeIncomePurchases
122350002
235520004
328410003
  • Sample — one customer. Each row is one sample.
  • Feature — one measurement. Each column is one feature: age, income, purchases.
  • Array — the numerical values, stored together with a shape.
  • Matrix — a two-dimensional array: samples × features.

Reveal the array when you can already point to samples and features in the table.

Reference: NumPy fundamentals · Python in a Web Worker

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