Network Internals

This chapter provides a collection of recipes regarding the internals of a neural network. This includes tensor decomposition, weight initialization, topology storage, bottleneck features, and corresponding embeddings.

We will cover the following recipes:

• Visualizing training with TensorBoard
• Analyzing network weights and more
• Freezing layers
• Storing the network topology and trained weights