Deep Learning for Numerical Applications with SAS by Henry Bequet
Requirements: .ePUB reader, 5.4 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://douploads.net/r9w13szl5jfm
(Closed Filehost) http://upload4earn.net/knds27d0zeda
Requirements: .ePUB reader, 5.4 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
https://douploads.net/r9w13szl5jfm
(Closed Filehost) http://upload4earn.net/knds27d0zeda