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Essentials of Data Science and Analytics: Statistical Tools, Machine Learning, and R-Statistical Software Overview - Softcover
Synopsis
This book combines the key concepts of data science and analytics to help you gain a practical understanding of these fields.
Data science and analytics have emerged as the most desired fields in driving business decisions. Using the techniques and methods of data science, decision makers can uncover hidden patterns in their data, develop algorithms and models that help improve processes and make key business decisions.
Data science is a data driven decision making approach that uses several different areas and disciplines with a purpose of extracting insights and knowledge from structured and unstructured data. The algorithms and models of data science along with machine learning and predictive modeling are widely used in solving business problems and predicting future outcomes.
This book combines the key concepts of data science and analytics to help you gain a practical understanding of these fields. The four different sections of the book are divided into chapters that explain the core of data science. Given the booming interest in data science, this book is timely and informative.
"synopsis" may belong to another edition of this title.
About the Author
Dr. Amar Sahay is a professor engaged in teaching, research, consulting, and training. He has a BS in production engineering (Birla Institute of Technology, India), MS in industrial engineering and a PhD in mechanical engineering –both from University of Utah, USA. He has taught/teaching at several Utah institutions including the University of Utah (school of engineering and management), SLCC, Westminster college, and others. Amar is a certified Six Sigma Master Black Belt and holds expert level certification in lean manufacturing/ lean management. He has contributed over 30 research papers in national and international conferences. Amar is the author of more than 10 professional and textbooks. Among his recent publications are Six Sigma Quality–Concepts and Cases, Statistics & Data Analysis Concepts, Managing and Improving Quality, Applied Regression & Modeling, Data Visualization, and Business Analytics/ Business Intelligence. He is also associated with QMS Global LLC; a company engaged in the areas of data visualization, analytics, lean six sigma, data analytics, manufacturing, and services systems analysis. Amar is a senior member of Institute of Industrial & Systems Engineers, and a senior member of American Society for Quality (ASQ).
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Essentials of Data Science and Analytics : Statistical Tools, Machine Learning, and R-Statistical Software Overview
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Essentials of Data Science and Analytics: Statistical Tools, Machine Learning, and R-Statistical Software Overview (Paperback or Softback)
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Essentials of Data Science and Analytics
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Paperback. Condition: New. This text provides a comprehensive overview of Data Science. With the continued advancement in storage and computing technologies, data science has emerged as one of the most desired fields in driving business decisions. Data science employs techniques and methods from many other fields, such as statistics, mathematics, computer science, and information science. Besides the methods and theories drawn from several fields, data science uses visualization techniques using specially designed big data software and statistical programming language, such as R programming, and Python. Data Science has wide applications in the areas of Machine Learning (ML) and Artificial Intelligence (AI). The book is divided into four different areas divided into different chapters. These chapters explain the core of Data Science. Part I of the book introduces the field of Data Science, different disciplines it comprises of, and the scope with future outlook and career prospects. This section also explains analytics, business analytics, and business intelligence and their similarities and differences with Data Science. Since the data is at the core of Data science, Part II is devoted to explaining the data, big data, and other features of data. One full chapter is devoted to Data Analysis, creating visuals, pivot table, and other applications using Excel with office 365. Part III explains the statistics behind Data Science. It uses several chapters to explain the statistics and its importance, numerical and data visualization tools and methods, probability, and probability distribution applications in Data Science. Other chapters in the Part III are Sampling, Estimation, and Hypothesis Testing. All these are integral part of Data Science applications. Part IV of the book provides the basics of Machine Learning (ML) and R-statistical software. Data Science has wide applications in the areas of Machine Learning (ML) and Artificial Intelligence (AI) and R-statistical software is widely used by data science professionals. The book also outlines a brief history, the body of knowledge, skills and education requirements for Data Scientist and data science professionals. Some statistics on job growth and prospects are also summarized. A career in data science is ranked at the third best job in America for 2020 by Glassdoor, and was ranked the number one best job from 2016-2019.[29]. Seller Inventory # LU-9781631573453
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Essentials of Data Science and Analytics: Statistical Tools in Data Science and Analytics-an Overview of Machine Learning and R-Statistical Software
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