Applied Analytics through Case Studies Using SAS and R - Deepti Gupta

Applied Analytics through Case Studies Using SAS and R (eBook)

Implementing Predictive Models and Machine Learning Techniques

(Autor)

eBook Download: PDF
2018 | 1st ed.
XX, 404 Seiten
Apress (Verlag)
978-1-4842-3525-6 (ISBN)
Systemvoraussetzungen
62,99 inkl. MwSt
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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.


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.
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 techniquesCreate and apply analytical strategiesWho This Book Is ForData 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.

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.

Applied Analytics through Case Studies Using SAS and RChapter 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

Erscheint lt. Verlag 3.8.2018
Zusatzinfo XX, 404 p. 99 illus.
Verlagsort Berkeley
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Netzwerke
Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Wirtschaft
Schlagworte Banking • Business Analytics • FMCG • Healthcare • machine learning • R • SAS • Telecom
ISBN-10 1-4842-3525-8 / 1484235258
ISBN-13 978-1-4842-3525-6 / 9781484235256
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