Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By : Nick McClure
Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By: 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)

An example of productionalizing TensorFlow

A good practice for productionalizing machine learning models is to separate the training and evaluation programs. In this section, we will illustrate an evaluation script that has been expanded to include a unit test, model saving and loading, and evaluation.

Getting ready

In this recipe, we will show you how to implement an evaluation script using the afore-mentioned criteria. The code actually consists of a training script and an evaluation script, but for this recipe we will only show you the evaluation script. As a reminder, both scripts can been seen in the online GitHub repository at https://github.com/nfmcclure/tensorflow_cookbook/ and at the official Packt repository: https...