Rewrite MLP colab to focus on batchnorm instead of dropout

[Charles Frye]

The issues with normalization are a great lead-in to introducing batchnorm, while dropout feels kinda tacked on.

Depending on timing, we could do both dropout and batchnorm -- presented as solutions to the two issues you see when you increase network depth, optimization problems and over-fitting.