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Apache Spark Deep Learning Cookbook

You're reading from   Apache Spark Deep Learning Cookbook Over 80 best practice recipes for the distributed training and deployment of neural networks using Keras and TensorFlow

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788474221
Length 474 pages
Edition 1st Edition
Languages
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Authors (2):
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Ahmed Sherif Ahmed Sherif
Author Profile Icon Ahmed Sherif
Ahmed Sherif
Amrith Ravindra Amrith Ravindra
Author Profile Icon Amrith Ravindra
Amrith Ravindra
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Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Spark for Deep Learning Development FREE CHAPTER 2. Creating a Neural Network in Spark 3. Pain Points of Convolutional Neural Networks 4. Pain Points of Recurrent Neural Networks 5. Predicting Fire Department Calls with Spark ML 6. Using LSTMs in Generative Networks 7. Natural Language Processing with TF-IDF 8. Real Estate Value Prediction Using XGBoost 9. Predicting Apple Stock Market Cost with LSTM 10. Face Recognition Using Deep Convolutional Networks 11. Creating and Visualizing Word Vectors Using Word2Vec 12. Creating a Movie Recommendation Engine with Keras 13. Image Classification with TensorFlow on Spark 14. Other Books You May Enjoy

Preparing dataset for the deep learning pipeline


We are now ready to prepare our dataset to be fed into the deep learning model that we will build in Keras.

Getting ready

While preparing the dataset for Keras we will import the following libraries into our notebook:

  • import pyspark.sql.functions as F
  • import numpy as np
  • from pyspark.ml.feature import StringIndexer
  • import keras.utils

How to do it...

This section walks through the following steps to prepare the dataset for the deep learning pipeline:

  1. Execute the following script to clean up the column names:
mainDF = mainDF.withColumnRenamed('userId_1', 'userid')
mainDF = mainDF.withColumnRenamed('movieId_1', 'movieid')
mainDF = mainDF.withColumnRenamed('rating_1', 'rating')
mainDF = mainDF.withColumnRenamed('timestamp_1', 'timestamp')
mainDF = mainDF.withColumnRenamed('imdbId', 'imdbid')
mainDF = mainDF.withColumnRenamed('tmdbId', 'tmdbid')
  1. The rating column is currently divided into 0.5 increments. Tweak the ratings to be rounded to a whole integer using...
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