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Hands-On Deep Learning with Apache Spark

You're reading from   Hands-On Deep Learning with Apache Spark Build and deploy distributed deep learning applications on Apache Spark

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788994613
Length 322 pages
Edition 1st Edition
Languages
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Author (1):
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Guglielmo Iozzia Guglielmo Iozzia
Author Profile Icon Guglielmo Iozzia
Guglielmo Iozzia
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Table of Contents (19) Chapters Close

Preface 1. The Apache Spark Ecosystem FREE CHAPTER 2. Deep Learning Basics 3. Extract, Transform, Load 4. Streaming 5. Convolutional Neural Networks 6. Recurrent Neural Networks 7. Training Neural Networks with Spark 8. Monitoring and Debugging Neural Network Training 9. Interpreting Neural Network Output 10. Deploying on a Distributed System 11. NLP Basics 12. Textual Analysis and Deep Learning 13. Convolution 14. Image Classification 15. What's Next for Deep Learning? 16. Other Books You May Enjoy Appendix A: Functional Programming in Scala 1. Appendix B: Image Data Preparation for Spark

Hands-on NLP with TensorFlow

In this section, we are going to use TensorFlow (Python) to do DL sentiment analysis using the same Large Movie Review Dataset as for the first example in the previous section. Prerequisites for this example are Python 2.7.x, the PIP package manager, and Tensorflow. The Importing Python Models in the JVM with DL4J section in Chapter 10, Deploying on a Distributed System, covers the details of setting up the required tools. We are also going to use the TensorFlow hub library (https://www.tensorflow.org/hub/), which has been created for reusable ML modules. It needs to be installed through pip, as follows:

pip install tensorflow-hub

The example also requires the pandas (https://pandas.pydata.org/) data analysis library, as follows:

pip install pandas

Import the necessary modules:

import tensorflow as tf
import tensorflow_hub as hub
import os
import...
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