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The decision maker's handbook to dat...

Kampakis, Stylianos.

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The decision maker's handbook to data science = a guide for non-technical executives, managers, and founders /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The decision maker's handbook to data science/ by Stylianos Kampakis.
其他題名:	a guide for non-technical executives, managers, and founders /
作者:	Kampakis, Stylianos.
出版者:	Berkeley, CA :Apress : : 2020.,
面頁冊數:	viii, 156 p. :ill., digital ;24 cm.
內容註:	Chapter 1: Demystifying Data Science and All the Other Buzzwords -- Chapter 2: Data Management -- Chapter 3: Data Collection Problems -- Chapter 4: How to Keep Data Tidy -- Chapter 5: Thinking like a Data Scientist (Without Being One) -- Chapter 6: A Short Introduction to Statistics -- Chapter 7: A Short Introduction to Machine Learning -- Chapter 8: Problem Solving -- Chapter 9: Pitfalls -- Chapter 10: Hiring and Managing Data Scientists -- Chapter 11: Building a Data-Science Culture -- Chapter 12: Epilogue: Data Science Rules the World -- Appendix A: Tools for Data Science.
Contained By:	Springer eBooks
標題:	Decision making - Data processing. -
電子資源:	https://doi.org/10.1007/978-1-4842-5494-3
ISBN:	9781484254943

The decision maker's handbook to data science = a guide for non-technical executives, managers, and founders /
Kampakis, Stylianos.

The decision maker's handbook to data sciencea guide for non-technical executives, managers, and founders /[electronic resource] :by Stylianos Kampakis. - Second edition. - Berkeley, CA :Apress :2020. - viii, 156 p. :ill., digital ;24 cm.

Chapter 1: Demystifying Data Science and All the Other Buzzwords -- Chapter 2: Data Management -- Chapter 3: Data Collection Problems -- Chapter 4: How to Keep Data Tidy -- Chapter 5: Thinking like a Data Scientist (Without Being One) -- Chapter 6: A Short Introduction to Statistics -- Chapter 7: A Short Introduction to Machine Learning -- Chapter 8: Problem Solving -- Chapter 9: Pitfalls -- Chapter 10: Hiring and Managing Data Scientists -- Chapter 11: Building a Data-Science Culture -- Chapter 12: Epilogue: Data Science Rules the World -- Appendix A: Tools for Data Science.

Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don't realize is that data science is in fact quite multidisciplinary-useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker's Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker's Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide.

ISBN: 9781484254943

Standard No.: 10.1007/978-1-4842-5494-3doiSubjects--Topical Terms:

752376
Decision making
--Data processing.

LC Class. No.: HD30.23 / .K367 2020

Dewey Class. No.: 005.73

The decision maker's handbook to data science = a guide for non-technical executives, managers, and founders /
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