This is a collection of slides and python code intended to introduce the user to Deep Neural Networks (DNNs) and their implementation using Keras. It considers three basic types: DNNs for regregression, DNNs for classification, and Convolutationl Neural Networks (CNNs) for image classification.
The python code is organized into Jupyter notebooks using Google Colaboratory. Each network is set up both as a "Challenge Problem" that suffers from some under- or overfitting, and as a "Possible Solution" that has settings that provide a fairly good fit. (Since GitHub sometimes struggles to display these Jupyter notebooks, the links to the Colab site are included below:)