Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report.
Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang, LinkedIn); venture capital (Roger Ehrenberg, IA Ventures); enterprise cloud computing and neuroscience (Eric Jonas, formerly Salesforce.com); newspaper and media (Chris Wiggins, The New York Times); streaming television (Caitlin Smallwood, Netflix); music forecast (Victor Hu, Next Big Sound); strategic intelligence (Amy Heineike, Quid); environmental big data (André Karpištšenko, Planet OS); geospatial marketing intelligence (Jonathan Lenaghan, PlaceIQ); advertising (Claudia Perlich, Dstillery); fashion e-commerce (Anna Smith, Rent the Runway); specialty retail (Erin Shellman, Nordstrom); email marketing (John Foreman, MailChimp); predictive sales intelligence (Kira Radinsky, SalesPredict); and humanitarian nonprofit (Jake Porway, DataKind). The book features a stimulating foreword by Google's Director of Research, Peter Norvig.
Each of these data scientists shares how he or she tailors the torrent-taming techniques of big data, data visualization, search, and statistics to specific jobs by dint of ingenuity, imagination, patience, and passion. Data Scientists at Work parts the curtain on the interviewees’ earliest data projects, how they became data scientists, theirdiscoveries and surprises in working with data, their thoughts on the past, present, and future of the profession, their experiences of team collaboration within their organizations, and the insights they have gained as they get their hands dirty refining mountains of raw data into objects of commercial, scientific, and educational value for their organizations and clients.Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Sebastian Gutierrez is a data entrepreneur who has founded three data-related companies: DataYou (data science and data visualization consulting and education), LetsWombat (data-driven product sampling), and Acheevmo (athletic performance statistics). He was formerly an emerging markets risk manager at Scotia Capital and an FX options trader at JP Morgan and Standard Chartered Bank.Gutierrez provides training in data visualization and D3.js to a diverse client base, including corporations such as the New York Stock Exchange, the American Express Company, and General Dynamics, universities, media agencies, and startups. He leads the 1,600-member New York City D3.js Meetup Group and is co-editor of Data Science Weekly, a weekly newsletter providing curated articles and videos on the latest developments in data science. He is a frequent speaker at meetups and conferences, such as Strata and Hadoop World in New York and Barcelona. He is a cross-disciplinary instructor at General Assembly. Gutierrez holds a BS in Mathematics from MIT and an MA in Economics from the University of San Francisco.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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