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Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley & SAS Business) (Englisch) Gebundene Ausgabe – 8. August 2014


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"...explains what it covers very well..." (ZDNet, September 2014)

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In today's business environment an endless stream of big data often shapes critical decision-making processes. To maintain and sustain a profitable business, it is imperative to harness the power of big data. However, simply accessing the data and having the ability to process it isn't enough to yield meaningful results.
 
Big Data, Data Mining, and Machine Learning offers marketing executives, business leaders, and technology experts a comprehensive resource for developing and implementing the strategies and methods that can consistently produce effective results and ultimately increase profitability. In this book, Jared Dean offers an accessible and thorough review of the current state of big data analytics and the growing trend toward high performance computing architectures. Big Data, Data Mining, and Machine Learning clearly shows how big data analytics can be leveraged to foster positive change and drive efficiency.
 
Step by step, Jared Dean reveals what it takes to use technology to create an analytical environment for data mining, machine learning, and working with big data. The author also explores the trade-offs that result from certain technology choices. Big Data, Data Mining, and Machine Learning includes a range of algorithms and methods that can be implemented to glean information from mined data and provides explanations on how to apply these approaches most effectively. Filled with illustrative case studies, the book offers myriad examples of successful organizations that have used new technological advances and algorithms to their competitive advantage. The author also includes a discussion of explanatory and predictive modeling and how these tools can be applied to the decision-making process.
 
For any organization that wants to access the power of data analytics, this important book can serve as a linchpin for understanding the underlying technology and analysis of big data. Now you can take control of your organization's big data analytics with confidence and create results that go directly to the bottom line.

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Amazon.com: 8 Rezensionen
4 von 4 Kunden fanden die folgende Rezension hilfreich
Well structured and easy to read, light on math 1. Oktober 2014
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
This is a well structured and easy to read book. As the title says, it discusses big data, data mining and machine learning and the potential value added to the business. The technical side, however, is light. There aren't many equations in the text and presented machine learning topics are rather high level. Overall, non-technical audience and lightly technical managers would benefit from the book, but those looking for heavy math and hands on data science should look elsewhere.
1 von 1 Kunden fanden die folgende Rezension hilfreich
by far was the most educating and beneficial book in the field to me 1. Juli 2014
Von Rayan Hafiz - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
For the past few months I bought many books in the field of Business Analytics, data mining, and big data. This one by far was the most educating and beneficial to my learning. It has very smooth language, very well written and organized and most importantly it explains the basic methods and concepts in data mining in a simple and easily understandable way with great introductional history on big data. I attended a presentation by the author few weeks back summarizing some ideas from the book and man I'm a fan. I told myself I wish if this guy was my instructor in collage as he is very good in delivering those not so easy concepts. Highly recommended if you really want to learn about data mining and big data.
1 von 1 Kunden fanden die folgende Rezension hilfreich
... introduces data mining and machine learning techniques in an easy to read and understandable format 18. November 2014
Von Susan Haller - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Jared did a remarkable job creating a book that introduces data mining and machine learning techniques in an easy to read and understandable format. His high level descriptions are complimented with real world examples that people of any technical background can understand and apply. This should be on the bookshelf of anyone in this field.
1 von 1 Kunden fanden die folgende Rezension hilfreich
Recommended 1. Juli 2014
Von Matthew Stevens - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
This book is terrific. Jared Dean takes a complicated subject and makes it easy to understand and thoroughly enjoyable. The writing is fluid and engaging. The use cases are enlightening, helping to shed light on the complex world of predictive analytics.
A must-read for any business leader that wants to remain competitive. 12. Januar 2015
Von Jim Foster - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
I came across this book while researching best practices for enterprise data mining. Over the 10+ years I lived and worked in Silicon Valley, I've created many databases, spreadsheets and scripts to turn operational data into actionable intelligence. While it was never the primary focus of my job, I did it to help me make better decisions, faster. I decided that if I was going to spend so much of my time mining data anyways, it would probably be worth my while to research how experts do it. Experts like Jared Dean.

This book is written with a clear, engaging style that makes it a pleasure to read -- quite an accomplishment given the subject matter. Part One of the book had just enough history and background to bring me up to speed with where the field stands and how we got here. By Part Two, the author dove deep into the nuts and bolts of how to tease business value out of big data. Many of the models, algorithms and methods covered in this section were completely new to me. The comprehensive yet concise treatment of this material has ignited my curiosity and illuminated many fresh avenues of exploration. The author wraps up with real-world success stories of businesses putting all these practices together and offers a provocative glimpse of what the future may hold.

For me, this book strikes the perfect balance between high-level theory and demonstrating practical tools, models and methods for wrangling enterprise data. Just knowing that these tools exist has life altering impact. If you are looking to deepen and broaden your understanding of Big Data, Data Mining and Machine Learning, there is no better book.
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