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Learning PySpark

You're reading from   Learning PySpark Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786463708
Length 274 pages
Edition 1st Edition
Languages
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Authors (2):
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Denny Lee Denny Lee
Author Profile Icon Denny Lee
Denny Lee
Tomasz Drabas Tomasz Drabas
Author Profile Icon Tomasz Drabas
Tomasz Drabas
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Toc

Table of Contents (13) Chapters Close

Preface 1. Understanding Spark FREE CHAPTER 2. Resilient Distributed Datasets 3. DataFrames 4. Prepare Data for Modeling 5. Introducing MLlib 6. Introducing the ML Package 7. GraphFrames 8. TensorFrames 9. Polyglot Persistence with Blaze 10. Structured Streaming 11. Packaging Spark Applications Index

What is TensorFlow?


TensorFlow is a Google open source software library for numerical computation using data flow graphs; that is, an open source machine learning library focusing on Deep Learning. Based loosely on neural networks, TensorFlow is the culmination of the work of Google's Brain Team researchers and engineers to apply Deep Learning to Google products and build production models for various Google teams including (but not limited to) search, photos, and speech.

Built on C++ with a Python interface, it has quickly become one of the most popular Deep Learning projects in a short amount of time. The following screenshot denotes a Google Trends comparison between four popular deep learning libraries; note the spike around November 8th - 14th, 2015 (when TensorFlow was announced) and the rapid rise over the last year (this snapshot was taken late December 2016):

Another way to measure the popularity of TensorFlow is to note that TensorFlow is the most popular machine learning framework...

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