Book Image

TensorFlow Machine Learning Cookbook. - Second Edition

By : Sujit Pal, Nick McClure
Book Image

TensorFlow Machine Learning Cookbook. - Second Edition

By: Sujit Pal, Nick McClure

Overview of this book

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Table of Contents (13 chapters)

Using TensorFlow Serving

In this section, we will show you how to set up your RNN model to predict spam or ham text messages on TensorFlow. We will first illustrate how to save a model in a protobuf format, and will then load the model into a local server, listening on port 9000 for input.

Getting ready

We start this section by encouraging reader to read through the official documentation and the short tutorials on the TensorFlow Serving site available at

For this example, we will reuse most of the RNN code we used in the on Predicting Spam with RNNs recipe in Chapter 9, Recurrent Neural Networks. We will alter our model saving code to save a protobuf model in the correct folder...