TensorFlow: Advanced Topics

Abstract

The TensorFlow library has come a long way from its first appearance. Especially in the last year, many more features have become available that can make the life of researchers a lot easier. Things like eager execution and Keras allow scientists to test and experiment much faster and debug models in ways that were not possible before. It is essential for any researcher to know those methods and know when it makes sense to use them. In this chapter, we will look at few of them: eager execution, GPU acceleration, Keras, how to freeze parts of a network and train only specific parts (used very often, especially in transfer learning and image recognition), and finally how to save and restore models already trained. Those technical skills will be very useful, not only to study this book, but in real-life research projects.