Deep Learning - Deep Neural Network for Beginners Using Python - Linear to Non-Linear Boundaries

The video discusses the limitations of linear solutions in classification problems, particularly when data is not linearly separable. It introduces the concept of nonlinear boundaries and suggests combining multiple linear boundaries to create a nonlinear boundary. The discussion includes examples of how different boundaries can be combined and the potential use of logical gates to achieve this. The video concludes with questions about the number of boundaries needed and the methods of combining them, setting the stage for further exploration of nonlinear solutions.

What are the limitations of using a linear solution for classification?

What criteria should be considered when deciding which employees to hire based on their academic and test records?

How can combining linear boundaries help in creating a nonlinear boundary?

Explain the concept of combining linear boundaries to achieve a nonlinear classification.

What types of gates can be used to combine different linear boundaries?