Anasse Bari & Mohamed Chaouchi 
Predictive Analytics For Dummies [PDF ebook] 

Sokongan

Use Big Data and technology to uncover real-world insights
You don’t need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you’ll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you’ll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you’ll develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get you stakeholder buy-in.
Big Data has taken the marketplace by storm, and companies are seeking qualified talent to quickly fill positions to analyze the massive amount of data that are being collected each day. If you want to get in on the action and either learn or deepen your understanding of how to use predictive analytics to find real relationships between what you know and what you want to know, everything you need is a page away!
* Offers common use cases to help you get started
* Covers details on modeling, k-means clustering, and more
* Includes information on structuring your data
* Provides tips on outlining business goals and approaches
The future starts today with the help of Predictive Analytics For Dummies.

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Mengenai Pengarang

Anasse Bari, Ph.D. is data science expert and a university professor who has many years of predictive modeling and data analytics experience.
Mohamed Chaouchi is a veteran software engineer who has conducted extensive research using data mining methods.
Tommy Jung is a software engineer with expertise in enterprise web applications and analytics.

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Bahasa Inggeris ● Format PDF ● Halaman-halaman 464 ● ISBN 9781119267027 ● Saiz fail 7.5 MB ● Penerbit John Wiley & Sons ● Diterbitkan 2016 ● Edisi 2 ● Muat turun 24 bulan ● Mata wang EUR ● ID 4979803 ● Salin perlindungan Adobe DRM
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