BizStore » Books » Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
Item Dimensions: Array
Number Of Items: 1
Number Of Pages: 368
Publication Date: 2016-01-20
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer
"The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com
Award-winning | Used by over 30 universities | Translated into 12 languages
An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques.
Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die.
How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more.
A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.
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• Predictive Analytics For Dummies, 2nd Edition
• Storytelling with Data: A Data Visualization Guide for Business Professionals
• The Caterpillar's Edge: Evolve, Evolve Again, and Thrive in Business
• Competing on Analytics: Updated, with a New Introduction: The New Science of Winning
• The Marketing Performance Blueprint: Strategies and Technologies to Build and Measure Business Success
• Keeping Up with the Quants: Your Guide to Understanding and Using Analytics
• Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (The MIT Press)
• Too Big to Ignore: The Business Case for Big Data (Wiley and SAS Business Series)