Complete the following:

  1. Open RStudio and use File -> Recent Projects to select and open the R Project which is managing your GitHub repository.

  2. Use File -> Open File... and navigate to the location of your R Markdown notebook from Competition Assignment 2. Open it.

  3. Add code to your setup chunk which will load any packages you want to use to build deep learning models. Run all of the code in your existing notebook.

  4. Return to your Model Construction and Interpretation section. Train at least one deep learning model. Are you able to outperform your best existing model or ensemble?

    • While Neural Networks are not known for their interpretability, be sure to discuss your modeling decisions (architecture, activation functions, etc.) and why you are making the choices you are making.

  5. Use your new model to make predictions on the properties in comp.csv. Submit those predictions to our class Kaggle competition for scoring.

  6. Add a Conclusions section to your analytics report.

    • We’ll omit the Executive Summary and Introduction sections from this analytics report, but you’ll include those sections in the analytics report corresponding to your final course project.

  7. When you are done, use the blue ball of yarn button to knit the notebook into an HTML document.

  8. Use the Git tab in the top right pane of RStudio to Pull, Commit, Push your new files to your remote repository at GitHub.

Stop by my office if you have any questions or need help.