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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

Practical applications of DL

The DL concepts and models that were illustrated in the previous two sections aren't just pure theory – practical applications have been implemented from them. DL excels at identifying patterns in unstructured data; most use cases are related to media such as images, sound, video, and text. Nowadays, DL is applied in a number of use case scenarios across different business domains, such as the following:

  • Computer vision: A number of applications in the automotive industry, facial recognition, motion detection, and real-time threat detection
  • NLP: Sentiment analysis in social media, fraud detection in finance and insurance, augmented search, and log analysis
  • Medical diagnosis: Anomaly detection, pathology identification
  • Search engines: Image searching
  • IoT: Smart homes, predictive analysis using sensor data
  • Manufacturing: Predictive maintenance...
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