Machine Learning with SAS Viya
Machine Learning with SAS Viya

Author: SAS Institute Inc.

Publisher: SAS Institute

Published: 2020-05-29

Total Pages: 309

ISBN-13: 1951685377

DOWNLOAD EBOOK

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

Exploring SAS Viya
Exploring SAS Viya

Author: Sas Education

Publisher:

Published: 2020-01-10

Total Pages: 126

ISBN-13: 9781642955880

DOWNLOAD EBOOK

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.

SAS Viya
SAS Viya

Author: Kevin D. Smith

Publisher: SAS Institute

Published: 2017-02-16

Total Pages: 306

ISBN-13: 1629608858

DOWNLOAD EBOOK

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. --

Machine Learning with SAS
Machine Learning with SAS

Author:

Publisher:

Published: 2019-06-21

Total Pages: 168

ISBN-13: 9781642954760

DOWNLOAD EBOOK

Machine learning is a branch of artificial intelligence (AI) that develops algorithms that allow computers to learn from examples without being explicitly programmed. Machine learning identifies patterns in the data and models the results. These descriptive models enable a better understanding of the underlying insights the data offers. Machine learning is a powerful tool with many applications, from real-time fraud detection, the Internet of Things (IoT), recommender systems, and smart cars. It will not be long before some form of machine learning is integrated into all machines, augmenting the user experience and automatically running many processes intelligently. SAS offers many different solutions to use machine learning to model and predict your data. The papers included in this special collection demonstrate how cutting-edge machine learning techniques can benefit your data analysis. Also available free as a PDF from sas.com/books.

End-to-End Data Science with SAS
End-to-End Data Science with SAS

Author: James Gearheart

Publisher: SAS Institute

Published: 2020-06-26

Total Pages: 255

ISBN-13: 1642958069

DOWNLOAD EBOOK

Learn data science concepts with real-world examples in SAS! End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-by-step. Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level by mastering SAS programming for machine learning models.

SAS Visual Analytics for SAS Viya
SAS Visual Analytics for SAS Viya

Author: SAS

Publisher: SAS Institute

Published: 2020-12-07

Total Pages: 362

ISBN-13: 1952365112

DOWNLOAD EBOOK

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.

Introduction to Statistical and Machine Learning Methods for Data Science
Introduction to Statistical and Machine Learning Methods for Data Science

Author: Carlos Andre Reis Pinheiro

Publisher: SAS Institute

Published: 2021-08-06

Total Pages: 169

ISBN-13: 1953329624

DOWNLOAD EBOOK

Boost your understanding of data science techniques to solve real-world problems Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need. No software is shown in the book, and mathematical details are kept to a minimum. This allows you to develop an understanding of the fundamentals of data science, no matter what background or experience level you have.

Tree-Based Machine Learning Methods in SAS Viya
Tree-Based Machine Learning Methods in SAS Viya

Author: Sharad Saxena

Publisher:

Published: 2022-02-21

Total Pages: 364

ISBN-13: 9781954846715

DOWNLOAD EBOOK

Discover how to build decision trees using SASViya! Tree-Based Machine Learning Methods in SASViya covers everything from using a single tree to more advanced bagging and boosting ensemble methods. The book includes discussions of tree-structured predictive models and the methodology for growing, pruning, and assessing decision trees, forests, and gradient boosted trees. Each chapter introduces a new data concern and then walks you through tweaking the modeling approach, modifying the properties, and changing the hyperparameters, thus building an effective tree-based machine learning model. Along the way, you will gain experience making decision trees, forests, and gradient boosted trees that work for you. By the end of this book, you will know how to: build tree-structured models, including classification trees and regression trees. build tree-based ensemble models, including forest and gradient boosting. run isolation forest and Poisson and Tweedy gradient boosted regression tree models. implement open source in SAS and SAS in open source. use decision trees for exploratory data analysis, dimension reduction, and missing value imputation.

Exploring SAS Viya
Exploring SAS Viya

Author: Sas Education

Publisher:

Published: 2019-06-14

Total Pages: 80

ISBN-13: 9781642954838

DOWNLOAD EBOOK

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.

Deep Learning for Numerical Applications with SAS (Hardcover Edition)
Deep Learning for Numerical Applications with SAS (Hardcover Edition)

Author: Henry Bequet

Publisher:

Published: 2019-08-16

Total Pages: 234

ISBN-13: 9781642953565

DOWNLOAD EBOOK

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