Название: Data Science Without Makeup: A Guidebook for End-Users, Analysts, and Managers
Автор: Mikhail Zhilkin
Издательство: CRC Press
Год: 2022
Страниц: 194
Язык: английский
Формат: True EPUB
Размер: 10,1 MB

What data science is? Since you are reading this book, one could safely assume you have got at least a vague idea about what data science is. However, the range of things people can mean when the say “data science” is rather broad, so it is best to make sure we are on the same page. The term “data science” is most often used to describe the discipline which extends the field of statistics to incorporate advances in computing. A “data scientist” is someone who applies data science to solve a wide range of problems, and the “scientist” part can be misleading to those unfamiliar with the terminology.

The Care and Feeding of Data Scientists, an excellent book on managing data science teams, defines four data scientist archetypes:
• Operational: applying data science to the everyday functioning of the business.
• Product-focused: working closely with a product team, needs to be business savvy, like the operational data scientist.
• Engineering: building and maintaining the systems that power the work of the product or operational data scientists.
• Research: tasked with advancing the state of the art, often in a field like deep learning or computer vision or natural language processing, without any explicit expectation that their work will be immediately useful to the company.
The kind of data science examined in this book is primarily done by operational and product-focused data scientists.

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players’ physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence. Why data science is hard, what pitfalls analysts and decision-makers fall into, and what everyone involved can do to give themselves a fighting chance―the book examines these and other questions with the skepticism of someone who has seen the sausage being made.

Honest and direct, full of examples from real life, Data Science Without Makeup: A Guidebook for End-Users, Analysts and Managers will be of great interest to people who aspire to work with data, people who already work with data, and people who work with people who work with data―from students to professional researchers and from early-career to seasoned professionals.

"Having worked with Mikhail it does not surprise me that he has put together a comprehensive and insightful book on Data Science where down-to-earth pragmatism is the recurring theme. This is a must-read for everyone interested in industrial data science, in particular analysts and managers who want to learn from Mikhail‘s great experience and approach." --Stefan Freyr Gudmundsson, Lead Data Scientist at H&M, former AI Research Lead at King and Director of Risk Analytics and Modeling at Islandsbanki.

"It tells the unvarnished truth about data science. Chapter 2 ("Data Science is Hard") is worth the price on its own―and then Zhilkin gives us processes to help. A must-read for any practitioner, manager, or executive sponsor of data science." --Ted Lorenzen, Director of Marketing Analytics at Vein Clinics of America