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TensorFlow Machine Learning Cookbook

TensorFlow Machine Learning Cookbook

By : Nick McClure
3.7 (18)
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TensorFlow Machine Learning Cookbook

TensorFlow Machine Learning Cookbook

3.7 (18)
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 will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow. This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.
Table of Contents (13 chapters)
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12
Index

Using Multiple Executors


It should be apparent to the reader that there are many features of TensorFlow and computational graphs that lend itself naturally to being computed in parallel. The computational graph can be broken up on different processors as well as processing different batches. We will address how to access different processors on the same machine in this recipe.

Getting ready

For this recipe, we will show how to access multiple devices on the same system and train on them. This is a very common occurrence, as along with a CPU, a machine may have one or more GPUs that can share the computationl load. If TensorFlow can access these devices, it will automatically distribute the computations to the multiple devices via a greedy process. But TensorFlow also allows the program to specify which operations will be on which devices via namescope placement.

In order to access GPU devices, the GPU version of TensorFlow must be installed. To install the GPU version of TensorFlow, visit https...

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