Deep Learning with R

Chapter 7. Advanced deep-learning best practices

This chapter covers

• The Keras functional API
• Using Keras callbacks
• Working with the TensorBoard visualization tool
• Important best practices for developing state-of-the-art models

This chapter explores a number of powerful tools that will bring you closer to being able to develop state-of-the-art models on difficult problems. Using the Keras functional API, you can build graph-like models, share a layer across different inputs, and use Keras models just like R functions. Keras callbacks and the TensorBoard browser-based visualization tool let you monitor models during training. We’ll also discuss several other best practices including batch normalization, residual connections, hyperparameter ...