End-to-End Data Science with SAS: A Hands-On Programming Guide

Author:   James Gearheart
Publisher:   SAS Institute
ISBN:  

9781642958041


Pages:   380
Publication Date:   30 June 2020
Format:   Paperback
Availability:   In stock   Availability explained
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End-to-End Data Science with SAS: A Hands-On Programming Guide


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Overview

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.

Full Product Details

Author:   James Gearheart
Publisher:   SAS Institute
Imprint:   SAS Institute
Dimensions:   Width: 19.10cm , Height: 2.00cm , Length: 23.50cm
Weight:   0.653kg
ISBN:  

9781642958041


ISBN 10:   1642958042
Pages:   380
Publication Date:   30 June 2020
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

Finally, a data science book that is not too technical or too complicated to understand! James Gearheart's new book, End-to-End Data Science with SAS(R): A Hands-On Programming Guide, is the right book at the right time. James does a great job of breaking down the complexity of data science projects into organized and manageable components so that anyone with a limited background or experience can benefit from his unique approach. James ties his strong understanding of the data in real-world applications to control data volume and apply advanced analytics to identify patterns and conclusions in the data. This is the perfect book for my Data Science with SAS class students since it will prepare them for the next generation of data automation and optimum research. The techniques learned from this book increase confidence in making important decisions while reducing risks. Sunil Gupta Founder of SASSavvy.com


Finally, a data science book that is not too technical or too complicated to understand! James Gearheart's new book, End-to-End Data Science with SAS(R) A Hands-On Programming Guide, is the right book at the right time. James does a great job of breaking down the complexity of data science projects into organized and manageable components so that anyone with a limited background or experience can benefit from his unique approach. James ties his strong understanding of the data in real-world applications to control data volume and apply advanced analytics to identify patterns and conclusions in the data. This is the perfect book for my Data Science with SAS class students since it will prepare them for the next generation of data automation and optimum research. The techniques learned from this book increase confidence in making important decisions while reducing risks. Sunil Gupta Founder of SASSavvy.com


Author Information

James Gearheart is an experienced Senior Data Scientist and Machine Learning Engineer who has developed transformative machine learning and artificial intelligence models. He has over 20 years of experience in developing and analyzing statistical models and machine learning products that optimize business performance across several industries including digital marketing, financial services, public health care, environmental services, social security and worker's compensation. James has been both a data science manager and an individual contributor on projects ranging from logistics, anti-money laundering, CRM, cash demand forecasting, customer segmentation, digital marketing, A/B testing, attribution and attrition. His research interests include applied data science, machine learning, and artificial intelligence.

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