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Coordinate change

A coordinate change transforms points or data from one coordinate system or reference frame into another while preserving the represented relationships.

How 2 Manning books explain it

Deep Learning with R, Third Edition

A coordinate change is a transformation that expresses points using a different coordinate system.

How it is used
Simplifies classification and recognition by expressing data in coordinates that expose an easier rule.
How deep it goes
Explains hand-designed point separation and Cartesian-to-polar conversion, but does not develop formal coordinate mathematics.
Examples
Uses black-and-white point classification and clock-hand angles as concrete transformation examples.
What you can do after
Apply it by redesigning input features so a simple rule or machine-learning algorithm can solve the task.

Read how Deep Learning with R, Third Edition explains coordinate change →

Deep Learning with Python, Third Edition

A transformation that converts data points into a different coordinate system to obtain a more useful representation.

How it is used
Frames representation design as a way to turn difficult classification or recognition problems into simple rules.
How deep it goes
Defines the transformation through point classification and clock recognition, but stops short of formal derivations.
Examples
Uses separated black-and-white points, handwritten-digit features, and Cartesian-to-polar clock-hand coordinates.
What you can do after
Apply via feature engineering to express data in coordinates that support simpler rules or reduce the need for learning.

Read how Deep Learning with Python, Third Edition explains coordinate change →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.