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Developing analytic talent: becoming a data scientist

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Developing analytic talent: becoming a data scientist

Developing analytic talent: becoming a data scientist

Becoming a Data Scientist

Parution le 02/05/2014

Résumé

Learn what it takes to succeed in the the most in-demand tech job

Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. With over 15 years of big data, predictive modeling, and business analytics experience, author Vincent Granville is no stranger to data science. In this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code.

The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one.

Explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms
Shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists Features job interview questions, sample resumes, salary surveys, and examples of job ads
Case studies explore how data science is used on Wall Street, in botnet detection, for online advertising, and in many other business-critical situations
Developing Analytic Talent: Becoming a Data Scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates.

L'avis du libraire

Learn what it takes to succeed in the the most in-demand tech job

L'auteur Vincent Granville

Vincent Granville, Ph.D. is a data scientist with 15 years of big data, predictive modeling, and business analytics experience. He is the co-founder of Data Science Central, which includes a robust editorial platform, social interaction, forum-based technical support, the latest in technology tools and trends, and industry job opportunities.

Sommaire

  • Chapter 1 What Is Data Science?
  • Real Versus Fake Data Science
  • Two Examples of Fake Data Science
  • The Face of the New University
  • The Data Scientist
  • Data Scientist Versus Data Engineer
  • Data Scientist Versus Statistician
  • Data Scientist Versus Business Analyst
  • Data Science Applications in 13 Real-World Scenarios
  • Scenario 1: DUI Arrests Decrease After
  • End of State Monopoly on Liquor Sales
  • Scenario 2: Data Science and Intuition
  • Scenario 3: Data Glitch Turns Data Into Gibberish
  • Scenario 4: Regression in Unusual Spaces
  • Scenario 5: Analytics Versus Seduction to Boost Sales
  • Scenario 6: About Hidden Data
  • Scenario 7: High Crime Rates Caused by Gasoline Lead. Really?
  • Scenario 8: Boeing Dreamliner Problems
  • Scenario 9: Seven Tricky Sentences for NLP
  • Scenario 10: Data Scientists Dictate What We Eat?
  • Scenario 11: Increasing Amazon.com Sales with Better Relevancy
  • Scenario 12: Detecting Fake Profiles or Likes on Facebook
  • Scenario 13: Analytics for Restaurants
  • Data Science History, Pioneers, and Modern Trends
  • Statistics Will Experience a Renaissance
  • History and Pioneers
  • Modern Trends
  • Recent Discussions
  • Summary
  • Chapter 2 Big Data Is Different
  • ...
Voir tout
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Caractéristiques techniques du livre "Developing analytic talent: becoming a data scientist"

  PAPIER
Éditeur(s) Wiley
Auteur(s) Vincent Granville
Parution 02/05/2014
Couverture Broché
Intérieur Noir et Blanc
EAN13 9781118810088
ISBN13 978-1-118-81008-8

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