Book Image

Learning PySpark

By : Tomasz Drabas, Denny Lee
Book Image

Learning PySpark

By: Tomasz Drabas, Denny Lee

Overview of this book

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.
Table of Contents (20 chapters)
Learning PySpark
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
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...