1. Recap: Machine Learning in the Tidyverse
Well done!
You've reached the final video of this course. Let's briefly review what you've learned.
2. Chapter 1 - The List Column Workflow
In chapter one you learned how to use the list column workflow. This workflow is the backbone of working with models in the tidyverse.
3. Chapter 2 - Explore Multiple Models With broom
In chapter 2 you leveraged this workflow to build models for each country in the gapminder dataset. You then learned about the various attributes of these models using the tidy(), glance() and augment() functions from the broom package.
4. Chapter 3 - Build, Tune & Evaluate Regression Models
In chapter 3 you learned about the train-validate-test approach and how it can be used to select and evaluate models. This introduced you to the functions from the rsample, Metrics and ranger packages.
5. Chapter 4 - Build, Tune & Evaluate Classification Models
Finally, in chapter 4 you learned how to apply the list column workflow to build, tune and evaluate classification models.
6. Congratulations!
Thank you for the time that you have dedicated to this course.
I find these methods and tools to be indispensable for my work as a data scientist and I hope that you will gain the same value for your work.
It has been a pleasure to work with you and I wish you the best of luck on your journey of learning.