Shifting gears away from the Space Shuttle, let's work through how to set up, train, and evaluate a deep learning model. You see these used quite a bit for image classification, NLP, and so on. However, let's look at using it for regression. You don't find too many examples of that in my opinion. As such, let's go with our Ames housing price data we used back in Chapter 2, Linear Regression. Before that, let's briefly discuss what Tensor, TensorFlow, and Keras are.
An example of deep learning
Keras and TensorFlow background
I mentioned earlier that Keras is an API, a frontend if you will, for several deep learning backends. It was originally available only for Python but has been available in R since...