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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

Introduction

Recurrent neural networks have proven to be incredibly efficient at tasks involving the learning and prediction of sequential data. However, when it comes to natural language, the question of long-term dependencies comes into play, which is basically remembering the context of a particular conversation, paragraph, or sentence in order to make better predictions in the future. For example, consider a sentence that says:

Last year, I happened to visit China. Not only was Chinese food different from the Chinese food available everywhere else in the world, but the people were extremely warm and hospitable too. In my three years of stay in this beautiful country, I managed to pick up and speak very good....

If the preceding sentence were fed into a recurrent neural network to predict the next word in the sentence (such as Chinese), the network would find it difficult since...

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