Download An Introduction To Sas Visual Analytics full books in PDF, epub, and Kindle. Read online free An Introduction To Sas Visual Analytics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Tricia Aanderud |
| Publisher | : SAS Institute |
| Total Pages | : 294 |
| Release | : 2017-03-21 |
| Genre | : Computers |
| ISBN | : 1635260442 |
Focusing on the version of SAS Visual Analytics on SAS 9.4, this thorough guide will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code ¿̐ư unless you want to. --
| Author | : SAS |
| Publisher | : SAS Institute |
| Total Pages | : 362 |
| Release | : 2020-12-07 |
| Genre | : Computers |
| ISBN | : 1952365112 |
Discover your data and create reports in an elegant and intuitive web-based interface! SAS Visual Analytics for SAS Viya is a practical guide designed to get you started investigating your data and creating reports with SAS Visual Analytics, a web-based tool that enables you to explore huge volumes of data to identify patterns, trends, and opportunities. Learn how to report, share, and collaborate on insights from data with no SAS programming skills necessary – this book is accessible to all, including decision makers, business analysts, report creators, and citizen data scientists. SAS Visual Analytics for SAS Viya first introduces the basics needed to prepare and explore your data, make discoveries, and create a report in SAS Visual Analytics. Then, the second section describes more advanced topics, such as using automated explanation and creating advanced interactive reports with parameters. The book covers: Adding and manipulating data items within SAS Visual Analytics Analyzing data with SAS Visual Analytics Designing and sharing reports using SAS Visual Analytics Demonstrations and practices are included for you to follow to gain hands-on experience with SAS Visual Analytics, and the data sets used in the book are also provided to download.
| Author | : Sas Education |
| Publisher | : |
| Total Pages | : 110 |
| Release | : 2019-06-28 |
| Genre | : |
| ISBN | : 9781642954906 |
Data visualization enables decision makers to see analytics presented visually so that they can grasp difficult concepts or identify new patterns. SAS offers several solutions for visualizing your data, many of which are powered by SAS Viya. This book includes four visualization solutions powered by SAS Viya: SAS Visual Analytics, SAS Visual Statistics, SAS Visual Text Analytics, and SAS Visual Investigator. SAS visualization software is designed for anyone in your organization who wants to use and derive insights from data-from influencers, decision makers, and analysts to statisticians and data scientists. Also available as a free e-book from sas.com/books.
| Author | : Sas Education |
| Publisher | : |
| Total Pages | : 80 |
| Release | : 2019-06-14 |
| Genre | : |
| ISBN | : 9781642954838 |
This first book in the series covers how to access data files, libraries, and existing code in SAS Studio. You also learn about new procedures in SAS Viya, how to write new code, and how to use some of the pre-installed tasks that come with SAS Visual Data Mining and Machine Learning. In the last chapter, you learn how to use the features in SAS Data Preparation to perform data management tasks using SAS Data Explorer, SAS Data Studio, and SAS Lineage Viewer. Also available free as a PDF from sas.com/books.
| Author | : Sas Education |
| Publisher | : |
| Total Pages | : 126 |
| Release | : 2020-01-10 |
| Genre | : Computers |
| ISBN | : 9781642955880 |
SAS Visual Data Mining and Machine Learning, powered by SAS Viya, means that users of all skill levels can visually explore data on their own while drawing on powerful in-memory technologies for faster analytic computations and discoveries. You can manually program with custom code or use the features in SAS Studio, Model Studio, and SAS Visual Analytics to automate your data manipulation and modeling. These programs offer a flexible, easy-to-use, self-service environment that can scale on an enterprise-wide level. In this book, we will explore some of the many features of SAS Visual Data Mining and Machine Learning including: programming in the Python interface; new, advanced data mining and machine learning procedures; pipeline building in Model Studio, and model building and comparison in SAS Visual Analytics.
| Author | : Kevin D. Smith |
| Publisher | : SAS Institute |
| Total Pages | : 306 |
| Release | : 2017-02-16 |
| Genre | : Computers |
| ISBN | : 1629608858 |
Taking you on a journey to learn and apply Python programming in the context of the SAS Viya platform, this book includes examples from creating connections to CAS all the way to simple statistics and machine learning. --
| Author | : SAS Institute Inc. |
| Publisher | : SAS Institute |
| Total Pages | : 295 |
| Release | : 2020-05-29 |
| Genre | : Computers |
| ISBN | : 1951685377 |
Master machine learning with SAS Viya! Machine learning can feel intimidating for new practitioners. Machine Learning with SAS Viya provides everything you need to know to get started with machine learning in SAS Viya, including decision trees, neural networks, and support vector machines. The analytics life cycle is covered from data preparation and discovery to deployment. Working with open-source code? Machine Learning with SAS Viya has you covered – step-by-step instructions are given on how to use SAS Model Manager tools with open source. SAS Model Studio features are highlighted to show how to carry out machine learning in SAS Viya. Demonstrations, practice tasks, and quizzes are included to help sharpen your skills. In this book, you will learn about: Supervised and unsupervised machine learning Data preparation and dealing with missing and unstructured data Model building and selection Improving and optimizing models Model deployment and monitoring performance
| Author | : Teresa Jade |
| Publisher | : SAS Institute |
| Total Pages | : 275 |
| Release | : 2019-03-29 |
| Genre | : Computers |
| ISBN | : 1635266610 |
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.
| Author | : |
| Publisher | : |
| Total Pages | : 108 |
| Release | : 2019-06-14 |
| Genre | : |
| ISBN | : 9781642954821 |
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.
| Author | : |
| Publisher | : |
| Total Pages | : 74 |
| Release | : 2020-08-31 |
| Genre | : |
| ISBN | : 9781952363184 |
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.
