Deep Learning Model With Neural Networks – Using ReLU With SGD

I have created a UML Class Model for Deep Learning With Neural Networks – Using ReLU (Rectified Linear Unit) With SGD (Stochastic Gradient Descent).

The Class Model is attached below as a PNG (Portable Network Graphics) image. Please click on the image to view it clearly in any browser.

This is an exercise in architecture and choosing a UML class model allowed me to provide an initial big-picture view for discussions. Anybody who wants to collaborate and/or help in this field is welcome to provide guidance.

I reverse engineered the code from a great book called “Neural Networks from Scratch in Python”. This book is wonderful because it follows the KISS Principle in using Python code and all the available libraries.

The UML tools I used were:

[1] https://pynsource.com/

and

[2] https://gituml.com/