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burk scott; miner gary d. - it's all analytics!

It's All Analytics! The Foundations of Al, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government

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Genere:Libro
Lingua: Inglese
Pubblicazione: 08/2022
Edizione: 1° edizione





Note Editore

It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, "analytics," is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.




Sommario

Foreword Number One. Foreword Number Two. Foreword Number Three. Preface. Endorsements. Authors. Chapter 1. You Need This Book. Chapter 2. Building a Successful Program. Chapter 3. Some Fundamentals – Process, Data, and Models. Chapter 4. It's All Analytics! Chapter 5. What Are Business Intelligence (BI) and Visual BI? Chapter 6. What Are Machine Learning and Data Mining? Chapter 7. AI (Artificial Intelligence) and How It Differs from Machine Learning. Chapter 8. What Is Data Science? Chapter 9. Big Data and Bigger Data, Little Data, Cloud, and Other Data. Chapter 10. Statistics, Causation, and Prescriptive Analytics. Chapter 11. Other Disciplines to Dive in Deeper: Computer Science, Management/Decision Science, Operations Research, Engineering (and More). Chapter 12. Looking Ahead. Index.




Autore

Scott Burk has been solving complex business and health care problems for twenty-five years through science, statistics, machine learning and business acumen. Scott started his career, well actually in analytics, as as an analytic chemist after graduating with a double major in biology and chemistry from Texas State University. He continued his education, going to school at night taking advanced courses in science and math at the University of Texas at Dallas (UTD). He then started programming at the toxicology lab where he was working and thus started taking computer science (CS) and business courses until he graduated with a Master’s in Business with a concentration in finance soon after from UTD. Texas Instruments (TI) hired him as a financial systems analyst in Semiconductor Group, but due to TI’s needs and Scott’s love of computers, he soon after became a systems analyst for corporate TI. He worked there for three years and started itching to get back to school (even though, he continued to take courses at night (Operations Research and CS) through TI’s generous educational program). TI granted him an educational leave of absence and he went to Baylor University to teach in the business school and get a PhD in statistics. He joined Baylor as a non-tenure track professor teaching Quantitative Business Analysis (today = business analytics). After graduating, Scott went back to TI as a Decision Support Manager for the consumer arm of TI (today = consulting data scientist). Where he engaged in many functional areas – marketing and sales, finance, engineering, logistics, customer relations the call center and more. It was a dream job, but unfortunately, TI exited that business. Scott joined Scott and White, a large integrated healthcare delivery system in Texas as a consulting statistician. He moved into an executive role as Associate Executive Director, Information Systems leading Data Warehousing, Business Intelligence and Quality Organizations working with clinics, hospitals and the health plan. At the same time, he received a faculty appointment and taught informatics with Texas A&M University. He left, but later came back to Baylor, Scott and White (BSW) as Chief Statistician for BSW Healthplan. Scott continued his education, getting an advanced management certification from Southern Methodist University (SMU) and Master’s Degree (MS) in Data Mining (machine learning) from Central Connecticut State University. Scott is a firm believer in life-long learning. He also worked as Chief Statistician at Overstock, re-engineering the way they tested and evaluated marketing campaigns and other programs (analytics, statistics). He launched their ‘total customer value’ program. He was a Lead Pricing Scientist (analytics, optimization) for a B2B pricing optimization company (Zilliant) for a number of years. He thoroughly enjoyed working with a rich diverse, well-educated group that affected the way he looks at multidisciplinary methods of solving problems. He was a Risk Manager for eBay/Paypal identifying fraud and other risks on the platform and payment system. He has been working the last few years supporting software development, marketing and sales, specifically data infrastructure, data science and analytics platforms for Dell and now TIBCO. He supports his desire to learn and keep current by writing and teaching in the Masters of Data Science Program at City University of New York. Dr. Gary Miner received his B.S. from Hamline University, St. Paul, Minnesota with biology, chemistry and education majors; M.S. in Zoology & Population Genetics from the University of Wyoming, and his Ph.D. in Biochemical Genetics from the University of Kansas as the recipient of a NASA Pre-Doctoral Fellowship. During the doctoral study years, he also studied mammalian genetics at The Jackson Laboratory, Bar Harbor, ME, under a College Training Program on an NIH award; and another College Training Program at the Bermuda Biological Station, St. George’s West, Bermuda in a Marine Developmental Embryology Course, on an NSF award; and a third College Training Program held at the University of California, San Diego at the Molecular Techniques in Developmental Biology Institute, again on an NSF award. Following that he studied as a Post-Doctoral student at the University of Minnesota in Behavioral Genetics, where, along with research in schizophrenia and Alzheimer’s Disease, he learned "how to write books" from assisting in editing two book manuscripts of his mentor, Irving Gottesman, Ph.D. (Dr. Gottesman returned the favor 41 years later by writing two tutorials for this PRACTICAL TEXT MINING book). After academic research and teaching positions, Dr. Miner did another two-year NIH-Post-Doctoral in Psychiatric Epidemiology and Biostatistics at the University of Iowa where he became thoroughly immersed in studying affective disorders and Alzheimer’s Disease. All together he spend over 30 years researching and writing papers and










Altre Informazioni

ISBN:

9780367493790

Condizione: Nuovo
Dimensioni: 10 x 7 in Ø 1.24 lb
Formato: Brossura
Illustration Notes:20 b/w images and 1 table
Pagine Arabe: 272
Pagine Romane: xxxvi


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