Interpret Artificial Neural Network Output

For this assignment, identify a practical problem that could be solved through the use of an artificial neural network and devise a solution where you identify the neural network algorithm to be used.
For example, you might select a basic feed-forward artificial neural network where the goal is to classify cases into any number of possible groups (e.g., low risk, moderate risk, high risk) based on a set of assumed input data, which could be structured numerical data, image data, etc. You will need to indicate which algorithm you will use (e.g., feed-forward, convolutional, or recurrent) as well as which activation function you will use (e.g., the sigmoid function, Tanh activation function, or the ReLU activation function).
In addition, you will create a PowerPoint presentation with a mocked-up output from the algorithm with corresponding interpretations that address the identified problem. To help guide you in determining what your output should look like, review the example in this week’s introduction about training accuracy and projected output (Python implementation of a feed-forward artificial neural network).
The PowerPoint presentation should include the following components:

Brief overview of the problem
Selection of an artificial neural network algorithm with sufficient justification for its selection
Mocked-up results with interpretations

The presentation should include visuals and brief narratives with speaker notes on each slide.
Length: 5-7 slides, not including title or reference slides
Slide Content: No more than 25 words per slide
Speaker Notes: Minimum of 100-250 words per page
References: Include a minimum of 5 scholarly resources