Present your Results

Summary

For the final assignment of this course, record an eight to twelve minute presentation of the applied machine learning model you will use as a prototype for your proposed future research plan. Your recorded presentation will be due by 5PM on August 8th.

Step 1. Write an abstract and give your presentation a title

Draft an abstract and give your presentation a title. Review and edit your abstract, which should be less than a page in length, single spaced. Post your abstract to your index in advance of the deadline.

Step 2. Prepare the slides for your presentation

Prepare to speak eight to twelve minutes and include at least one presentation slide that addresses each of the following elements from your work.

  • A problem statement that introduces your selected topic, identifies significant goals associated with the implementation of your applied machine learning method, demonstrates why your problem is important, and describes and analyzes the complex nature of your problem including any process oriented causes and effects. Conclude your problem statement with a stated central research question. You are welcome to articulate a central research question in broad and general terms, given the abbreviated time frame for this investigation.

  • A description of the data that you are using as input for your applied machine learning methodology, including the source of the data, the different features (variables) and well as their data class (i.e. continuous or discrete). Be sure to include a description of your dataset size (number of rows / observations as well as number of columns / variables / features) and provide context on how the data was collected as well as the source.

  • Provide the specification for your applied machine learning model that presented the most promise in providing a solution to your problem. Include the section from your script that specifies your model architecture. Provide a brief description of how you implemented your code in practice.

  • Conclude with a section that preliminarily assesses model performance. If you have results from your implementation, you are welcome to add those in this section. Compare your preliminary results with those from the literature on your topic for a comparative assessment. If you are not able to produce preliminary results, provide a cursory literature review that includes 2 sources that present and describes their validation. With more time and project support, estimate what an ideal outcome looks like in terms of model validation.

Step 3. Record your presentation

Record your eight to twelve minute long presentation and provide a link to it via your zoom or panopto folder on your GitHub index. Using any combined screen and audio recording device is perfectly acceptable (Mac, Windows, Linux). Send your link to me as a message in slack in advance of the August 8th deadline.