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his section of your final report should describe how your model performed and provide evidence for how your work did/did not support your experimental hypothesis

his section of your final report should describe how your model performed and provide evidence for how your work did/did not support your experimental hypothesis or solve your chosen problem. The reader should be able to answer the following questions:

  • How effective was your machine learning model(s) at learning the task? e.g. Did the model(s) overfit/underfit the training data? What does the training accuracy/loss curve(s) look like for your model(s)?
  • If your project is focused on answering a research question, what evidence do you have to support or disprove your hypothesis?
  • If your project is focused on solving a problem, how will your model performance affect the application of your model to that problem?
  • Did your models training or performance bring about any unexpected results?
  • If you were to continue this project, what would your next steps be? e.g. Would you continue to optimize your model(s) or try other model architectures? Would you change or expand the data used in your model? What steps need to be taken to productionize your model?

You may not be completely finished with your model optimization this week, but your submission this week should demonstrate significant progress on model evaluation and optimization. As such, your submitted draft can include notes/bullet points about how you will answer any of the questions listed above in place of complete prose. You are expected to update this section of your report before submitting it as a part of your final report. You should be building up your works cited as you submit each of the pieces of your final report throughout the course, so be sure to include all of your citations/references in your submission each week.

  • Submit your APA-formatted draft as a PDF document

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