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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

NLP

NLP is the field of using computer science and AI to process and analyze natural language data and then make machines able to interpret it as humans do. During the 1980s, when this concept started to get hyped, language processing systems were designed by hand coding a set of rules. Later, following increases in calculation power, a different approach, mostly based on statistical models, replaced the original one. A later ML approach (supervised learning first, also semi-supervised or unsupervised at present time) brought advances in this field, such as voice recognition software and human language translation, and will probably lead to more complex scenarios, such as natural language understanding and generation.

Here is how NLP works. The first task, called the speech-to-text process, is to understand the natural language received. A built-in model performs speech recognition...

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