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Data Mining For Business Analytics: Concepts, Techniques, And Applications With Jmp Pro
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Data Mining For Business Analytics: Concepts, Techniques, And Applications With Jmp Pro Presents An Applied And Interactive Approach To Data Mining.Featuring Handson Applications With Jmp Pro, A Statistical Package From The Sas Institute, The Bookuses Engaging, Realworld 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 Endofchapter Examples And Exercises That Allow Readers To Expand Their Comprehension Of The Presented Material Datarich 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 Www.Dataminingbook.Comdata Mining For Business Analytics: Concepts, Techniques, And Applications With Jmp Pro Is An Excellent Textbook For Advanced Undergraduate And Graduatelevel Courses On Data Mining, Predictive Analytics, And Business Analytics. The Book Is Also A Oneofakind 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 Datarich Field.
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- Q: What are the dimensions of the book? A: The book measures seven point zero one inches in length, one point two four inches in width, and ten inches in height. This size makes it suitable for easy handling and storage.
- Q: How many pages does the book have? A: The book has four hundred sixty-four pages. This length allows for a comprehensive exploration of data mining concepts and techniques.
- Q: What type of binding does the book use? A: The book is bound in hardcover. This durable binding enhances the book’s longevity and makes it suitable for regular use.
- Q: Who is the author of this book? A: The author of the book is Shmueli. His expertise in data analytics lends credibility to the content presented.
- Q: What is the main focus of the book? A: The main focus of the book is on data mining for business analytics. It covers concepts, techniques, and applications relevant to the field.
- Q: How can I use this book for learning? A: You can use this book as a textbook for advanced undergraduate and graduate-level courses on data mining. It includes exercises and case studies for practical learning.
- Q: Is this book suitable for beginners? A: No, this book is not primarily designed for beginners. It is more suited for advanced undergraduate and graduate-level students or professionals.
- Q: What types of examples does the book provide? A: The book includes real-world examples and case studies. These examples illustrate various applications of data mining techniques across different fields.
- Q: How do I keep the book in good condition? A: To keep the book in good condition, store it in a cool, dry place and handle it gently. Avoid exposure to direct sunlight to prevent fading.
- Q: Are there any online resources available with the book? A: Yes, there is a companion website available with additional resources. It includes over two dozen datasets, exercises, and solutions for instructors.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact the retailer for their return policy. Most retailers will offer a replacement or refund.
- Q: Is the book useful for data scientists? A: Yes, the book is a valuable resource for data scientists. It covers essential techniques and applications relevant to various data-rich fields.
- Q: What topics are covered in the book? A: The book covers topics such as predictive models, data visualization, clustering, and time series forecasting. Each chapter focuses on key data mining methods.
- Q: Does the book include exercises for practice? A: Yes, the book includes end-of-chapter examples and exercises. These are designed to enhance understanding and allow for practical application of the concepts.
- Q: Can this book be used in business analytics courses? A: Yes, this book is excellent for business analytics courses. It provides an applied approach to data mining techniques relevant to the business sector.
- Q: Is there a website for additional materials related to the book? A: Yes, there is a dedicated website at www.dataminingbook.com. It provides access to additional datasets, exercises, and instructor resources.