Introduction

Throughout this book, we have seen that TensorFlow is capable of implementing many models, but there is more that TensorFlow can do. This chapter will show you a few of those things. We'll start by showing how to use the various aspects of TensorBoard, a capability that comes with TensorFlow that allows us to visualize summary metrics, graphs, and images even while our model is training. The remaining recipes in the chapter will show how to use TensorFlow's group() function to do step-wise updates. This function will allow us to implement a genetic algorithm, perform k-means clustering, solve a system of ODEs, and even create a gradient boosted random forest.