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)

Implementing DeepDream

Another use for trained CNNs is exploiting the fact that some intermediate nodes detect features of labels (for instance, a cat's ear, or a bird's feather). Using this fact, we can find ways to transform any image to reflect those node features for any node we choose. For this recipe, we will go through the DeepDream tutorial on TensorFlow's website, but we will cover the essential parts in much more detail. The hope is that we can prepare the reader to use the DeepDream algorithm to explore CNNs, and features created in them.

Getting ready

TensorFlow's official tutorials show how to implement DeepDream through a script (refer to the first bullet point in the next See also section...