Final Report

A. Creating the final report

After making the predictions on the testing dataset, we can create the final report for the project. The report contains all major parts of the project, including data analysis, model overview, and results from training, evaluation, and predictions. The best way to present the report is through a slideshow presentation, which allows us to convey results with meaningful visualizations (e.g. plots, charts, etc.). Each slide should have limited text.

The project report should focus more on the data and results, rather than the machine learning model. It’s good to have an overview of the model’s architecture, but avoid going too in-depth into how the model actually works. A short description of the model and diagram of the architecture should be enough.

To see what this project’s report looks like, check out the presentation in the right-hand column of the screen.