concept yHat in category machine learning

This is an excerpt from Manning's book Machine Learning in Action. Login to get full access to this book.

The variable ws is now our weights, which we multiply by our constant tern, and the second one we multiply by our input variable X1. Because we’re assuming X0=1, we’ll get y=ws[0]+ws[1]*X1. We also want to call this predicted y something other than the actual data, so this is called yHat. Let’s compute yHat with our new ws: