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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

Predicting Apple Stock Market Cost with LSTM

Stock market predictions have been going on for many years and it has spawned an entire industry of prognosticators. It shouldn't come as a surprise since it can turn a significant profit if predicted properly. Understanding when is a good time to buy or sell a stock is key to getting the upper hand on Wall Street. This chapter will focus on creating a deep learning model using LSTM on Keras to predict the stock market quote of AAPL.

The following recipes will be covered in this chapter:

  • Downloading stock market data for Apple
  • Exploring and visualizing stock market data for Apple
  • Preparing stock data for model performance
  • Building the LSTM model
  • Evaluating the LSTM model
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