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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

What to expect next for deep learning and AI

As mentioned previously, there are daily advances in technology and there's a growing availability of greater, but at the same time cheaper, computational power, along with a greater availability of data, which is driving toward the implementation of deeper and more complex models. So, at the same time, the limit for both DL and AI seems to be the sky. Trying to understand what we have to expect for these fields is speculation that could help us clearly understand what would happen in a short period of time (2-3 years), but what can happen next could be less predictable, as it has been observed that any new idea in this space is bringing up other ideas and is contributing to radically transforming ways of doing business in several areas. So, what I am going to describe in this section is related to the immediate future rather than...

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