Data Science Without Makeup

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A01=Alessandro Fusco
A01=Mikhail Zhilkin
A12=Livia de Simone
Age Group_Uncategorized
Age Group_Uncategorized
Author_Alessandro Fusco
Author_Mikhail Zhilkin
automatic-update
business intelligence analytics
Candy Crush
Category1=Non-Fiction
Category=KC
Category=KJMB
Category=KJMV2
Category=PBT
Category=UB
Category=UDB
Category=UN
Category=UY
Chief Data Officer
Code Review
cognitive bias analysis
COP=United Kingdom
CSV File
Data Dredging
Data Science
Data Science Skills
Data Science Team
Data Set
Data Warehouse Team
data-driven decision making
Delivery_Delivery within 10-20 working days
English Premier League
eq_bestseller
eq_business-finance-law
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Face To Face
Follow
Game Start
Goal Achievement Framework
Hiring Manager
Hiring Process
Information Bias
Job Ad
KPI
Language_English
Make Up
Optimism Bias
PA=Available
Part III
performance measurement methods
Price_€50 to €100
PS=Active
QA Process
real-world data science challenges
softlaunch
sports analytics techniques
statistical pitfalls
Vice Versa

Product details

  • ISBN 9780367523220
  • Weight: 520g
  • Dimensions: 156 x 234mm
  • Publication Date: 02 Nov 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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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.

Mikhail Zhilkin is a data scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting.

Mikhail Zhilkin is a Data Scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting.

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