Description: Product Description : Data Mining for Business Analytics: Concepts, Techniques and Applications in Python Data Mining for Business Analytics Concepts Techniques and Applications in Python presents an applied approach to data mining concepts and methods using Python software for illustrationReaders will learn how to implement a variety of popular data mining algorithms in Python a free and opensource software to tackle business problems and opportunitiesThis is the sixth version of this successful text and the first using Python It covers both statistical and machine learning algorithms for prediction classification visualization dimension reduction recommender systems clustering text mining and network analysis It also includes A new coauthor Peter Gedeck who brings both experience teaching business analytics courses using Python and expertise in the application of machine learning methods to the drugdiscovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA undergraduate diploma and executive courses and from their students More than a dozen case studies demonstrating applications for the data mining techniques described Endofchapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets and instructor materials including exercise solutions PowerPoint slides and case solutionsData Mining for Business Analytics Concepts Techniques and Applications in Python is an ideal textbook for graduate and upperundergraduate level courses in data mining predictive analytics and business analytics This new edition is also an excellent reference for analysts researchers and practitioners working with quantitative methods in the fields of business finance marketing computer science and information technologyThis book has by far the most comprehensive review of business analytics methods that I have ever seen covering everything from classical approaches such as linear and logistic regression through to modern methods like neural networks bagging and boosting and even much more business specific procedures such as social network analysis and text mining If not the bible it is at the least a definitive manual on the subjectGareth M James University of Southern California and coauthor with Witten Hastie and Tibshirani of the bestselling book An Introduction to Statistical Learning with Applications in R( it is an used product )
Price: 96.81 USD
Location: Houston, Texas
End Time: 2024-09-10T08:00:16.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Brand: Shmueli, Galit
UPC: 9781119549840
MPN: Not Specified
Model No: Not Specified
Country of Origin: USA United States
Net Quantity/Number of Units: 1
Dimensions LxWxH - Cms: 7.2X1.2X10.1
ISBN-10: 1119549841
ISBN-13: 9781119549840
SKU: SONG1119549841
Edition: 1
No. of Pages: 608
Book Title: Data Mining for Business Analytics: Concepts, Techniques and Appl
Number of Pages: 608 Pages
Language: English
Publication Name: Data Mining for Business Analytics : concepts, Techniques and Applications in Python
Publisher: Wiley & Sons, Incorporated, John
Item Height: 1.1 in
Publication Year: 2019
Subject: Probability & Statistics / General, Commerce
Type: Textbook
Item Weight: 39.3 Oz
Item Length: 10.1 in
Subject Area: Mathematics, Business & Economics
Author: Nitin R. Patel, Peter Gedeck, Peter C. Bruce, Galit Shmueli
Item Width: 7.2 in
Format: Hardcover
