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210823 ||| eng |
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|a 9781119741763
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|a 9781119741718
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|a 1119741769
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|a 1119741718
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4 |
|a QA76.9.D343
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| 100 |
1 |
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|a Gutman, Alex J.
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| 245 |
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|a Becoming a data head
|b how to think, speak, and understand data science, statistics, and machine learning
|c Alex J. Gutman, Jordan Goldmeier
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| 260 |
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|a Indianapolis, Indiana
|b John Wiley & Sons Inc.
|c 2021
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| 300 |
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|a xxv, 226 pages
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| 505 |
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|a Introduction -- Part I. Thinking like a data head. What is the problem? -- What is data? -- Prepare to think statistically -- Part II. Speaking like a data head. Explore the data -- Examine the probabilities -- Challenge the statistics -- Part III. Understanding the data scientist’s toolbox. Search for hidden groups -- Understand the regression model -- Understand the classification model -- Understand text analytics -- Conceptualize deep learning -- Part IV. Ensuring success. Watch out for pitfalls -- Know the people and personalities -- What’s next?
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| 505 |
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|a Includes bibliographical references and index
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| 653 |
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|a Data mining / fast
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| 653 |
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|a Data Mining
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| 653 |
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|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
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| 653 |
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|a Machine learning / fast
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| 653 |
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|a Apprentissage automatique
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| 653 |
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
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|a Exploration de données (Informatique)
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| 653 |
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|a Machine Learning
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| 700 |
1 |
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|a Goldmeier, Jordan
|e author
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 015 |
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|a GBC1C2345
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| 776 |
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|z 9781119741749
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| 776 |
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|z 1119741718
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| 776 |
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|z 1119741769
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| 776 |
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|z 1119741742
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| 776 |
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|z 9781119741718
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| 776 |
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|z 9781119741763
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| 856 |
4 |
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|u https://learning.oreilly.com/library/view/~/9781119741749/?ar
|x Verlag
|3 Volltext
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| 082 |
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|a 006.312
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| 520 |
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|a “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.”--Publisher’s description
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| 520 |
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|a 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; and 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
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