This page describes the second of six project milestones.
You are encouraged to discuss these items with the professor and other students as you are working on this assignment. I am glad to help you with ideas on any parts that you’re finding especially challenging.
This should be one of the last things you write. For an assignment of this scope, it should be less than a page in length, highlighting what will be done and summarizing key conclusions that you will draw in the later sections.
You may update your list of references from the last assignment if desired.
In this section, include a subsection for each reference summarizing the key points that are relevant to your project. You want to provide enough discussion to let the reader know how this reference will be helpful to your project (or turned out not to be).
After reading this section, the reader should understand what work you plan and what software tools you plan to use (likely including MATLAB Deep Learning Toolbox or another framework as specified on the previous assignment). The level of detail should be sufficient so that if you were unavailable for a couple of weeks another student with similar background to you could begin work on the project in the direction you intend.
For example, are you focusing on implementing and evaluating a DNN (then you’d discuss key planned blocks of the model, input transformations, desired accuracy, etc.), or is this already done and you plan to focus on modifying the network to achieve some goal, use transfer learning to solve a related problem, and/or investigate model quantization and deployment on some particular platform, etc.?
From this section, the reader should understand the data you plan to use. They should either have confidence that a large amount (roughly defined) of data exists or understand your general plan to deal with limited data. Some questions you’ll probably need to answer include: