Data Mining For Business Analytics: Concepts, Techniques, And Applications With JMP Pro Download Free (EPUB, PDF)
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the bookuses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® also includes: Detailed summaries that supply an outline of key topics at the beginning of each chapter End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material Data-rich case studies to illustrate various applications of data mining techniques A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field. Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks, and book chapters, including Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition, also published by Wiley. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective and co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner ®, Third Edition, both published by Wiley. Mia Stephens is Academic Ambassador at JMP®, a division of SAS Institute. Prior to joining SAS, she was an adjunct professor of statistics at the University of New Hampshire and a founding member of the North Haven Group LLC, a statistical training and consulting company. She is the co-author of three other books, including Visual Six Sigma: Making Data Analysis Lean, Second Edition, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years. He is co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition, also published by Wiley.
File Size: 17909 KB
Print Length: 454 pages
Page Numbers Source ISBN: 1118877438
Publisher: Wiley; 1 edition (May 11, 2016)
Publication Date: May 11, 2016
Sold by: Digital Services LLC
Language: English
ASIN: B01FL4BH24
Text-to-Speech: Enabled
X-Ray: Not Enabled
Word Wise: Enabled
Lending: Not Enabled
Enhanced Typesetting: Not Enabled
Best Sellers Rank: #292,450 Paid in Kindle Store (See Top 100 Paid in Kindle Store) #35 in Kindle Store > Kindle eBooks > Business & Money > Economics > Econometrics #56 in Kindle Store > Kindle eBooks > Business & Money > Management & Leadership > Planning & Forecasting #91 in Kindle Store > Kindle eBooks > Business & Money > Economics > Statistics
I purchased the Kindle version of this book, only to find tables cut off on the right margin and many bitmapped equations that were very difficult to read. I returned it, as I expect to be able to actually view the books I purchase. This has been a recurring problem with many Kindle mathematics books. They never seem to be able to get it right, and they seldom offer a sample that is large enough to assess the quality issues before purchase.I'm giving the book 5 stars, because this is not the fault of the authors and I didn't want to unfairly penalize the overall content ratings.
I have taught, and teach, a two-course data mining sequence for the MBA business analytics specialization at my university using Dr. Shmueli’s Data Mining for Business Analytics and Practical Time Series Forecasting textbooks. Both the supporting materials and the textbooks are high-quality products that match up well with the mathematical facility and technical skills of my students. The exposition is accessible to students with a wide range of backgrounds, and balanced between enough mathematics to explain the methods but not so much that it raises barriers to understanding. I looked far and wide for comparable texts, but I know of no other combination that meets the needs of my students as well as these two texts. I unhesitatingly recommend them both.
Kindle edition textbooks should be exact replicas of the actual paper textbook, with page numbers and layout that are identical. If one needs to increase the size of the text image or figures, then a simple two-finger gesture to zoom the image should be adequate. This Kindle edition is constructed in the same poor fashion that electronic textbooks used to be in that the text can be enlarged, but there are no page numbers. The resolution of enlarged figures is very, very poor. , how can you continue to provide sub optimal Kindle versions of textbooks that actually need to be read by students and scholars? There is no acceptable excuse for this. Unless you absolutely need the Kindle version due to your situation (I live overseas and am enrolled in an online MBA program...receiving textbooks by mail is simply not practical), then I strongly discourage you from buying this edition. Only if it sells poorly will and the publisher realize that they need to pony up and do a better job. It should be astonishingly easy to do so. Again, DO NOT BUY THIS KINDLE EDITION.
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro Analytics: Data Science, Data Analysis and Predictive Analytics for Business (Algorithms, Business Intelligence, Statistical Analysis, Decision Analysis, Business Analytics, Data Mining, Big Data) Data Analytics: What Every Business Must Know About Big Data And Data Science (Data Analytics for Business, Predictive Analysis, Big Data) RapidMiner: Data Mining Use Cases and Business Analytics Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) Data Analytics: Practical Data Analysis and Statistical Guide to Transform and Evolve Any Business. Leveraging the Power of Data Analytics, Data ... (Hacking Freedom and Data Driven) (Volume 2) Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications) Analytics: Data Science, Data Analysis and Predictive Analytics for Business Healthcare Data Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More Data Management Essentials Using SAS and JMP Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data Business Plan: Business Tips How to Start Your Own Business, Make Business Plan and Manage Money (business tools, business concepts, financial freedom, ... making money, business planning Book 1) Agile Data Science: Building Data Analytics Applications with Hadoop Data Analysis and Data Mining using Microsoft Business Intelligence Tools: Excel 2010, Access 2010, and Report Builder 3.0 with SQL Server Bitcoin Mining: The Bitcoin Beginner's Guide (Proven, Step-By-Step Guide To Making Money With Bitcoins) (Bitcoin Mining, Online Business, Investing for ... Beginner, Bitcoin Guide, Bitcoin Trading) Data Mining and Analysis: Fundamental Concepts and Algorithms Exploratory Data Mining and Data Cleaning
