Becoming a Data Head (PDF)
How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
(Sprache: Englisch)
"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful."
Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage
You've heard the hype...
Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage
You've heard the hype...
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"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful."
Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage
You've heard the hype around data--now get the facts.
In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it.
You'll learn how to:
* Think statistically and understand the role variation plays in your life and decision making
* Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace
* Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence
* Avoid common pitfalls when working with and interpreting data
Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you'll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head--an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage
You've heard the hype around data--now get the facts.
In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it.
You'll learn how to:
* Think statistically and understand the role variation plays in your life and decision making
* Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace
* Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence
* Avoid common pitfalls when working with and interpreting data
Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you'll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head--an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
Autoren-Porträt von Alex J. Gutman, Jordan Goldmeier
ALEX J. GUTMAN, PhD, is a Data Scientist, Corporate Trainer, and Accredited Professional Statistician. His professional focus is on statistical and machine learning and he has extensive experience working as a Data Scientist for the Department of Defense and two Fortune 50 companies.JORDAN GOLDMEIER is a Data Scientist, author, speaker, and community leader. He is a seven-time recipient of the Microsoft Most Valuable Professional Award and he has taught analytics to members of the Pentagon and Fortune 500 companies.
Bibliographische Angaben
- Autoren: Alex J. Gutman , Jordan Goldmeier
- 2021, 1. Auflage, 272 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1119741769
- ISBN-13: 9781119741763
- Erscheinungsdatum: 13.04.2021
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Größe: 3.83 MB
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Sprache:
Englisch
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