Deep Learning - Deep Neural Network for Beginners Using Python - 3D Feature Space

The video tutorial explores the concept of dimensionality in data analysis, starting with a simple scenario involving two features and expanding to higher dimensions. It explains the transition from using a line to separate data in two dimensions to employing a hyperplane in three dimensions. The tutorial covers the mathematical representation of hyperplanes and how they are used for decision making in higher dimensions. It concludes by discussing the challenges of working with spaces of even higher dimensions.

What are the two initial features considered in the scenario?

How does the introduction of a third feature change the representation of the data?

What is the significance of a hyperplane in higher dimensional spaces?

Explain how the equation changes when moving from a line to a plane.

What challenges arise when dealing with spaces of four or more dimensions?