Deep Learning - Crash Course 2023 - Regression Problem

The video tutorial covers solving a regression problem using the Boston Housing dataset. It explains data preprocessing with scaling, building a neural network with specific layers and activation functions, and training the model using K-fold validation. The tutorial also discusses evaluating model performance using mean absolute error and addresses overfitting issues. Finally, it summarizes the application of deep learning models to regression problems.

How do you interpret the mean absolute error (MAE) in the context of this regression model?

What is K-fold validation and why is it used?

What steps are taken to prevent overfitting during model training?

What was the final mean absolute error achieved by the model, and what does it signify?