Natural Language Processing With Sas


Natural Language Processing With Sas
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Natural Language Processing With Sas


Natural Language Processing With Sas
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Author :
language : en
Publisher:
Release Date : 2020-08-31

Natural Language Processing With Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-31 with categories.


Natural Language Processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and emulate written or spoken human language. NLP draws from many disciplines including human-generated linguistic rules, machine learning, and deep learning to fill the gap between human communication and machine understanding. The papers included in this special collection demonstrate how NLP can be used to scale the human act of reading, organizing, and quantifying text data.



Natural Language Processing With Sas


Natural Language Processing With Sas
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Author :
language : en
Publisher:
Release Date : 2020

Natural Language Processing With Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.




Sas Text Analytics For Business Applications


Sas Text Analytics For Business Applications
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Author : Teresa Jade
language : en
Publisher: SAS Institute
Release Date : 2019-03-29

Sas Text Analytics For Business Applications written by Teresa Jade and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.


Extract actionable insights from text and unstructured data. Information extraction is the task of automatically extracting structured information from unstructured or semi-structured text. SAS Text Analytics for Business Applications: Concept Rules for Information Extraction Models focuses on this key element of natural language processing (NLP) and provides real-world guidance on the effective application of text analytics. Using scenarios and data based on business cases across many different domains and industries, the book includes many helpful tips and best practices from SAS text analytics experts to ensure fast, valuable insight from your textual data. Written for a broad audience of beginning, intermediate, and advanced users of SAS text analytics products, including SAS Visual Text Analytics, SAS Contextual Analysis, and SAS Enterprise Content Categorization, this book provides a solid technical reference. You will learn the SAS information extraction toolkit, broaden your knowledge of rule-based methods, and answer new business questions. As your practical experience grows, this book will serve as a reference to deepen your expertise.



Sas Or Technical Report


Sas Or Technical Report
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Author : SAS Institute
language : en
Publisher:
Release Date : 1997

Sas Or Technical Report written by SAS Institute and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Nonlinear programming categories.


Getting started; Syntax; Details; Examples.



Text Mining And Analysis


Text Mining And Analysis
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Author : Dr. Goutam Chakraborty
language : en
Publisher: SAS Institute
Release Date : 2014-11-22

Text Mining And Analysis written by Dr. Goutam Chakraborty and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-22 with Computers categories.


Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program.



Text Analytics With Sas


Text Analytics With Sas
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Author :
language : en
Publisher:
Release Date : 2019-06-14

Text Analytics With Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-14 with categories.


SAS provides many different solutions to investigate and analyze text and operationalize decisioning. Several impressive papers have been written to demonstrate how to use these techniques. We have carefully selected a handful of these from recent Global Forum contributions to introduce you to the topic and let you sample what each has to offer. Also available free as a PDF from sas.com/books.



Unstructured Data Analysis


Unstructured Data Analysis
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Author : Matthew Windham
language : en
Publisher: SAS Institute
Release Date : 2018-09-14

Unstructured Data Analysis written by Matthew Windham and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-14 with Computers categories.


Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data. This book covers the five critical elements of entity extraction, unstructured data, entity resolution, entity network mapping and analysis, and entity management. By following examples of how to apply processing to unstructured data, readers will derive tremendous long-term value from this book as they enhance the value they realize from SAS products.



Computer Vision With Sas


Computer Vision With Sas
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Author : Susan Kahler
language : en
Publisher:
Release Date : 2020-07-22

Computer Vision With Sas written by Susan Kahler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-22 with Computers categories.


Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. In recent years, computer vision has begun to rival and even surpass human visual abilities in many areas. SAS offers many different solutions to train computers to "see" by identifying and classifying objects, and several groundbreaking papers have been written to demonstrate these techniques. The papers included in this special collection demonstrate how the latest computer vision tools and techniques can be used to solve a variety of business problems.



Deep Learning For Numerical Applications With Sas


Deep Learning For Numerical Applications With Sas
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Author : Henry Bequet
language : en
Publisher: SAS Institute
Release Date : 2018-07-20

Deep Learning For Numerical Applications With Sas written by Henry Bequet and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-20 with Computers categories.


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.



Techniques And Environments For Big Data Analysis


Techniques And Environments For Big Data Analysis
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Author : B. S.P. Mishra
language : en
Publisher: Springer
Release Date : 2016-02-05

Techniques And Environments For Big Data Analysis written by B. S.P. Mishra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-05 with Technology & Engineering categories.


This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.