Book Image

R for Data Science

By : Dan Toomey
Book Image

R for Data Science

By: Dan Toomey

Overview of this book

Table of Contents (19 chapters)

Questions


Factual

  • Which supervised learning technique(s) do you lean towards as your "go to" solution?

  • Why are the density plots for Bayesian results off-center?

When, how, and why?

  • How would you decide on the number of clusters to use?

  • Find a good rule of thumb to decide the number of hidden layers in a neural net.

Challenges

  • Investigate other blind signal separation techniques, such as ICA.

  • Use other methods, such as poisson, in the rpart function (especially if you have a natural occurring dataset).