Think Like a Data Scientist: Tackle the Data Science Process Step-By-Step

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9781633430273: Think Like a Data Scientist: Tackle the Data Science Process Step-By-Step
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Summary

Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there.

About the Book

Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you'll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you'll put this knowledge together using a structured process for data science. When you've finished, you'll have a strong foundation for a lifetime of data science learning and practice.

What's Inside

  • The data science process, step-by-step
  • How to anticipate problems
  • Dealing with uncertainty
  • Best practices in software and scientific thinking

About the Reader

Readers need beginner programming skills and knowledge of basic statistics.

About the Author

Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups.

Table of Contents

    PART 1 - PREPARING AND GATHERING DATA AND KNOWLEDGE

  1. Philosophies of data science
  2. Setting goals by asking good questions
  3. Data all around us: the virtual wilderness
  4. Data wrangling: from capture to domestication
  5. Data assessment: poking and prodding
  6. PART 2 - BUILDING A PRODUCT WITH SOFTWARE AND STATISTICS

  7. Developing a plan
  8. Statistics and modeling: concepts and foundations
  9. Software: statistics in action
  10. Supplementary software: bigger, faster, more efficient
  11. Plan execution: putting it all together
  12. PART 3 - FINISHING OFF THE PRODUCT AND WRAPPING UP

  13. Delivering a product
  14. After product delivery: problems and revisions
  15. Wrapping up: putting the project away

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

L'autore:

Brian Godsey holds a PhD in applied mathematics, is active in the academic community, and has been developing statistical software for over 10 years. In the last few years, he has been involved in startups as a co-founder, adviser, and team member.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

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Brian Godsey
Editore: Manning Publications, United States (2017)
ISBN 10: 1633430278 ISBN 13: 9781633430273
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Valutazione libreria

Descrizione libro Manning Publications, United States, 2017. Paperback. Condizione: New. Language: English. Brand new Book. Data science is more than just a set of tools and techniques for extracting knowledge from data sets and data streams. Data science is also a process of getting from goals and questions to real, valuable outcomes by exploring, observing, and manipulating a world of data. Traversing this world can be difficult and confusing. Software developers and non-technical folks may struggle with the uncertainty and fuzzy answers that data invariably provide, and statisticians may have trouble working with any of the multitude of relevant software tools that lie outside of their expertise. Others may not even know where to begin. Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. This book helps you fill in conceptual knowledge gaps in the daunting fields of statistics and software development, and relates those skills to the real concerns of data science in the business world. As you work though the many practical examples, you'll use your existing knowledge of statistics and programming to solve real problems in data science. Key Features:Following the data science process data science, step by step* Discovering the world of data as a wilderness to be explored, wrangled, and studied Learning to foresee problems at each stage of a data science project * Dealing with the uncertainty inherent in working with data * Understanding concepts of data, software, and statistics in ways accessible even for beginners * Engaging in some of the most relevant best practices in software, statistics, and scientific thinking Readers should have some familiarity with a programming language and basic statistics, but need not be experts. Important foundational concepts will be reviewed briefly in the book. ABOUT THE TECHNOLOGY Data science is a set of concepts and techniques for extracting meaning and clarity from stored data sets or data streams. Codice articolo AAK9781633430273

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Brian Godsey
Editore: Manning Publications, United States (2017)
ISBN 10: 1633430278 ISBN 13: 9781633430273
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Valutazione libreria

Descrizione libro Manning Publications, United States, 2017. Paperback. Condizione: New. Language: English. Brand new Book. Data science is more than just a set of tools and techniques for extracting knowledge from data sets and data streams. Data science is also a process of getting from goals and questions to real, valuable outcomes by exploring, observing, and manipulating a world of data. Traversing this world can be difficult and confusing. Software developers and non-technical folks may struggle with the uncertainty and fuzzy answers that data invariably provide, and statisticians may have trouble working with any of the multitude of relevant software tools that lie outside of their expertise. Others may not even know where to begin. Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. This book helps you fill in conceptual knowledge gaps in the daunting fields of statistics and software development, and relates those skills to the real concerns of data science in the business world. As you work though the many practical examples, you'll use your existing knowledge of statistics and programming to solve real problems in data science. Key Features:Following the data science process data science, step by step* Discovering the world of data as a wilderness to be explored, wrangled, and studied Learning to foresee problems at each stage of a data science project * Dealing with the uncertainty inherent in working with data * Understanding concepts of data, software, and statistics in ways accessible even for beginners * Engaging in some of the most relevant best practices in software, statistics, and scientific thinking Readers should have some familiarity with a programming language and basic statistics, but need not be experts. Important foundational concepts will be reviewed briefly in the book. ABOUT THE TECHNOLOGY Data science is a set of concepts and techniques for extracting meaning and clarity from stored data sets or data streams. Codice articolo BTA9781633430273

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