Deep Learning for Numerical Applications with SAS

Henry Bequet

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English

SAS Institute
20 July 2018

Enterprise software; Mathematical & statistical software

Foreword by Oliver Schabenberger, PhD

Executive Vice President, Chief Operating Officer and Chief Technology Officer SAS

Dive into deep learning! Machine learning and deep learning are ubiquitous in our homes and workplaces-from machine translation to image recognition and predictive analytics to autonomous driving. Deep learning holds the promise of improving many everyday tasks in a variety of disciplines. Much deep learning literature explains the mechanics of deep learning with the goal of implementing cognitive applications fueled by Big Data. This book is different. Written by an expert in high-performance analytics, Deep Learning for Numerical Applications with SAS introduces a new field: Deep Learning for Numerical Applications (DL4NA). Contrary to deep learning, the primary goal of DL4NA is not to learn from data but to dramatically improve the performance of numerical applications by training deep neural networks.

Deep Learning for Numerical Applications with SAS presents deep learning concepts in SAS along with step-by-step techniques that allow you to easily reproduce the examples on your high-performance analytics systems. It also discusses the latest hardware innovations that can power your SAS programs: from many-core CPUs to GPUs to FPGAs to ASICs.

This book assumes the reader has no prior knowledge of high-performance computing, machine learning, or deep learning. It is intended for SAS developers who want to develop and run the fastest analytics. In addition to discovering the latest trends in hybrid architectures with GPUs and FPGAS, readers will learn how to

Use deep learning in SAS

Speed up their analytics using deep learning

Easily write highly parallel programs using the many task computing paradigms

This book is part of the SAS Press program.

By: Henry Bequet
Imprint: SAS Institute
Dimensions: Height: 235mm, Width: 191mm, Spine: 12mm
Weight: 408g
ISBN: 9781635266801
ISBN 10: 1635266807
Pages: 234
Publication Date: 20 July 2018
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Henry Bequet is Director of High-Performance Computing and Machine Learning in the Financial Risk division of SAS. In that capacity, he leads the development of a high-performance solution that can run SAS code on thousands of CPU and GPU cores for advanced models that use techniques like Black-Scholes, Binomial Evaluation, and Monte-Carlo simulations. Henry has more than 35 years of industry experience and 15 years of high-performance analytics practice. He has published two books and several papers on server development and machine learning.

Reviews for Deep Learning for Numerical Applications with SAS

This book is an information and detailed-rich reference that also provides step-by-step guidance to teach and highlight areas of high-performance analytics of SAS Viya and supporting applications. It instills curiosity and provides guidance to the novice to advance SAS programmer, so they can develop and run the fastest analytics. -- Michelle Homes, Metacoda Australia