Deep Learning - Deep Neural Network for Beginners Using Python - Data Analysis NN (Neural Networks) Implementation

The video tutorial introduces neural networks, starting with a simple model to build intuition. It covers importing necessary libraries like Pandas and Numpy, and reading data from a CSV file. The data includes features such as GRE scores, GPA, and rank, with the target being admission status. The tutorial demonstrates data visualization using Matplotlib and discusses the importance of including rank as a feature. It highlights the need for scaling features due to mismatched scales and suggests one-hot encoding for categorical data like rank.

How are the scatter plots used to visualize the data of admitted and rejected students?

What challenges are presented by the data when trying to create a solution boundary?

Describe the process of one-hot encoding and its relevance in this context.