Final Project Deliverables: Due Wednesday May 13

By | May 12, 2020

All deliverables should be put in your group’s folder on Googledocs by  Wednesday May 13 and should be uploaded to the shared google drive folder except for the code. See below for details on submission of your code.

Part 1:  Literature Review:

  • Deliverable:  The slides you presented Tuesday, Apr. 29.  Summarize the main points you made for each slide in the notes.
  • If you did not use slides, you still need to create a slide set with the points you made on each of the 3 papers.
  • Include how this research related to the topic  you are working on and what you learned from the literature review that impacted or guided the rest of your project (implementation and/or data analysis).
  • Your final slide should  be the references.

Part 2& 3:  Implementation and  Data analysis

  • Deliverables:
    • Final presentation (see outline below).  Submit the slides with notes.
    • For data analysis:
      • 2-3 page write up on your data analysis.  Include what data you used, what you were looking for, and what you found with specific examples from the data.  (Include lots of examples with short descriptions of what they showed you).
    • For implementation:
      • If you built a dialog system, submit the Dialogflow json and the code for the dialog manager/back end
      • Otherwise submit any code you wrote.
      • If your codebase lives on github, gitlab, or any other similar repository-as-service, create a txt file with the link to the repository.
        • If your codebase is private, in a sense that only registered collaborator can access, you should invite “keighrim” to the repository.
    • Presentation outline.   Presentations will be 20-25 minutes, so plan accordingly in order to be able to cover all 4 areas. (I realize you all did very different kinds projects, so adjust these areas to fit what you did).
      • Define the problem you were working on, illustrating with examples of your analysis
      • Present a demonstration of the system you built.
      • Describe where it was successful and where it was not able to handle cases, again using examples from your data analysis
      • Conclude with lessons learned.  How could the field move towards improvements in the area you are focusing on (you can take  points from your research presentations and/or your own ideas on what directions to take.


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