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Predictive Analytics For Dummies (For Dummies Series) Paperback – Import, 24 Mar 2014
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From the Back Cover
- Analyze structured and unstructured data
- Use algorithms and data analysis techniques
- Build clustering, classification and statistical models
- Apply predictive analytics to your website and marketing efforts
A practical guide to using Big Data and technology to discover real–world insights
Predict the future! Data is growing exponentially and predictive analytics is your organization s key to making use of it to create a competitive advantage. This comprehensive resource will help you define real–world projects and takes a step–by–step approach to the technical aspects of predictive analytics so you can get up and running right away.
- Enter the arena jump into predictive analytics by discovering how data can translate to a competitive advantage
- Incorporating algorithms discover data models, how to identify similarities and relationships, and how to predict the future through data classification
- Developing a roadmap prepare your data, create goals, structure and process your data, and build a predictive model that will get stakeholder buy–in
- Programming predictive analytics use in–depth tips to install software, modules, and libraries to get going with prediction models
- Making predictive analytics work gain an understanding of the typical pushback on predictive analytics adoption and how to overcome it
Open the book and find:
- Real–world tips for creating business value
- Common use cases to help you get started
- Details on modeling, k–means clustering, and more
- How you can predict the future with classification
- Information on structuring your data
- Methods for testing models
- Hands–on guides to software installation
- Tips on outlining business goals and approaches
About the Author
Dr. Anasse Bari is a Fulbright scholar, a software engineer, and a data mining expert. Mohamed Chaouchi has conducted extensive research using data mining methods in both health and financial domains. Tommy Jung has worked extensively on natural language processing and algorithmic trading using machine learning.
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