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Applied Analytics through Case Studies Using SAS and R

Implementing Predictive Models and Machine Learning Techniques

Deepti Gupta

$116.95   $93.60

Paperback

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English
APress
04 August 2018
Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.   This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data.  The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms.  Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills.  What You'll Learn  

Understand analytics and basic data concepts 

Use an analytical approach to solve Industrial business problems 

Build predictive model with machine learning techniques

Create and apply analytical strategies

Who This Book Is For

Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.

By:  
Imprint:   APress
Country of Publication:   United States
Edition:   1st ed.
Dimensions:   Height: 254mm,  Width: 178mm, 
Weight:   802g
ISBN:   9781484235249
ISBN 10:   148423524X
Pages:   404
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Chapter 1: Role of Analytics in Various Industries.- Chapter 2:  Banking Case Study with Analytical Solutions.- Chapter 3:  Retail Case Study with Analytical Solutions.- Chapter 4:  Telecommunication Case Study with Analytical Solutions.- Chapter 5:  Healthcare Case Study with Analytical Solutions.- Chapter 6: Airline Case Study with Analytical Solutions.- Chapter 7:  FMCG Case Study with Analytical Solutions. 

Deepti Gupta completed her MBA in Finance and PGPM in operation research in 2010. She has worked with KPMG and IBM private limited as Data Scientist and is currently working as a data science freelancer. Deepti has extensive experience in predictive modeling and machine learning with an expertise in SAS and R. Deepti has developed data science courses, delivered data science trainings, and conducted workshops for both corporate and academic institutions. She has written multiple blogs and white papers. Deepti has a passion for mentoring budding data scientists.

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