SAS Viya: The Python Perspective - Softcover

Smith, Kevin D.; Meng PhD, Xiangxiang

Softcover

ISBN 10: 1629602760 ISBN 13: 9781629602769

Publisher: SAS Institute, 2017

Synopsis

Learn how to access analytics from SAS Cloud Analytic Services (CAS) using Python and the SAS^Ū Viya^™ platform.

SAS^Ū Viya^™: The Python Perspective is an introduction to using the Python client on the SAS Viya platform. SAS Viya is a high-performance, fault-tolerant analytics architecture that can be deployed on both public and private cloud infrastructures. While SAS Viya can be used by various SAS applications, it also enables you to access analytic methods from SAS, Python, Lua, and Java, as well as through a REST interface using HTTP or HTTPS.

This book focuses on the perspective of SAS Viya from Python. SAS Viya is made up of multiple components. The central piece of this ecosystem is SAS Cloud Analytic Services (CAS). CAS is the cloud-based server that all clients communicate with to run analytical methods. The Python client is used to drive the CAS component directly using objects and constructs that are familiar to Python programmers.

Some knowledge of Python would be helpful before using this book; however, there is an appendix that covers the features of Python that are used in the CAS Python client. Knowledge of CAS is not required to use this book. However, you will need to have a CAS server set up and running to execute the examples in this book.

With this book, you will learn how to:

• Install the required components for accessing CAS from Python
• Connect to CAS, load data, and run simple analyses
• Work with CAS using APIs familiar to Python users
• Learn about general CAS workflows and advanced features of the CAS Python client

SAS^Ū Viya^™: The Python Perspective covers topics that will be useful to beginners as well as experienced CAS users. It includes examples from creating connections to CAS all the way to simple statistics and machine learning, but it is also useful as a desktop reference.

About this title

About the Authors

Kevin D. Smith has been a software developer at SAS since 1997. He has been involved in the development of PROC TEMPLATE and other underlying ODS technologies for most of his tenure. He has spoken at numerous SAS Global Forum conferences, as well as at regional and local SAS users groups with the a oeFrom Scratcha  series of presentations that were created to help users of any level master various ODS technologies. More recently, he has been involved in the creation of the scripting language interfaces to SAS Cloud Analytic Services on the SAS Viya platform.

Xiangxiang Meng, PhD, is a Senior Product Manager at SAS. The current focus of his work is on SAS Visual Statistics, cognitive computing, the Python interface to SAS Cloud Analytic Services, and other new product initiatives. Previously, Xiangxiang worked on SAS LASR Analytic Server, SAS In-Memory Statistics for Hadoop, SAS Recommendation Systems, and SAS Enterpriser Miner. His research interests include decision trees and tree ensemble models, automated and cognitive pipelines for business intelligence and machine learning, and parallelization of machine learning algorithms on distributed data. Xiangxiang received his PhD and MS from the University of Cincinnati.

Edition details

• Publisher: SAS Institute
• Publication date: 2017
• Language: English
• ISBN 10: 1629602760
• ISBN 13: 9781629602769
• Binding: Paperback
• Edition number: 1
• Number of pages: 306