Introduction

In the previous chapter, you learned how to load and process a variety of data types so that they can be used in TensorFlow modeling. This included tabular data from CSV files, image data, text data, and audio files. By the end of the chapter, you were able to process all these data types and produce numerical tensors from them that can be input for model training.

In this chapter, you will learn about TensorFlow resources that will aid you in your model building and help you create performant machine learning algorithms. You will explore the practical resources that practitioners can utilize to aid their development workflow, including TensorBoard, TensorFlow Hub, and Google Colab. TensorBoard is an interactive platform that offers a visual representation of the computational graphs and data produced during the TensorFlow development process. The platform solves the problem of visualizing various data types that is common in machine learning. The visualization toolkit...