Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Data Scientists at Work

Buy
Data Scientists at Work, 9781430265986 (1430265981), Apress, 2014

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); oceanographic 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). 

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, their discoveries 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.

Readers will learn:
  • How the data scientists arrived at their positions and what advice they have for others
  • What projects the data scientists work on and the techniques and tools they apply
  • How to frame problems that data science can solve
  • Where data scientists think the most exciting opportunities lie in the future of data science
  • How data scientists add value to their organizations and help people around the world
Who this book is for
The primary readership for this book is general-interest readers interested in this hot new profession and in the nature of the people who work up the readers' own data trails. The secondary readerships are (a) scientists, mathematicians, and students in feeder disciplines who are interested in scouting the vocational prospects and daily working conditions of data scientists with a view to becoming data scientists themselves, and (b) of business colleagues and managers seeking to understand and collaborate with data scientists to integrate their data management and interpretation capabilities into the competitive intelligence capabilities of the enterprise.

Table of Contents
Chapter 1. Chris Wiggins (The New York Times)
Chapter 2. Caitlin Smallwood (Netflix)
Chapter 3. Yann LeCun (Facebook)
Chapter 4. Erin Shellman (Nordstrom)
Chapter 5. Daniel Tunkelang (LinkedIn)
Chapter 6. John Foreman (MailChimp)
Chapter 7. Roger Ehrenberg (IA Ventures)
Chapter 8. Claudia Perlich (Dstillery)
Chapter 9. Jonathan Lenaghan (PlaceIQ)
Chapter 10. Anna Smith (Rent The Runway)
Chapter 11. Andre Karpistsenko (Planet OS)
Chapter 12. Amy Heineike (Quid)
Chapter 13. Victor Hu (Next Big Sound)
Chapter 14. Kira Radinsky (SalesPredict)
Chapter 15. Eric Jonas (Independent Scientist)
Chapter 16. Jake Porway (DataKind)
(HTML tags aren't allowed.)

Inside the Box: Leading With Corporate Values to Drive Sustained Business Success
Inside the Box: Leading With Corporate Values to Drive Sustained Business Success

How to turn company values into competitive advantage

We are inclined, for whatever reason, to treat values like works of art. We view them as nice to hang on the wall, and beautiful to look at, but we don’t act as though they truly mean much to us in the real world. In fact, the opposite is true. The best...

Service Oriented Architecture: An Integration Blueprint
Service Oriented Architecture: An Integration Blueprint

Successfully implement your own enterprise integration architecture using the Trivadis Integration Architecture Blueprint

Overview of Service Oriented Architecture: An Integration Blueprint

  • Discover and understand the structure of existing application landscapes from an integration perspective
  • ...
Pro .NET 2.0 XML (Expert's Voice in .Net)
Pro .NET 2.0 XML (Expert's Voice in .Net)
XML is the de facto language for communication within and between distributed applications, whether they're on the Internet or a corporate network. XML is successful because of two strengths: it has a highly-structured human readable format and it can be transmitted as pure text. No matter how disparate applications and their architectures may be,...

The Business Guide to Sustainability: Practical Strategies and Tools for Organizations
The Business Guide to Sustainability: Practical Strategies and Tools for Organizations

First edition: Winner of Choice Magazine - Outstanding Academic Titles for 2007 Sustainability promises both reduced environmental impacts and real cash savings for any organization - be it a business, non-profit/NGO or government department. This easy-to-use manual has been written by top business consultants specifically to help managers,...

Ant Colony Optimization and Constraint Programming
Ant Colony Optimization and Constraint Programming

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts.

...
JBoss at Work: A Practical Guide
JBoss at Work: A Practical Guide

Consisting of a number of well-known open source products, JBoss is more a family of interrelated services than a single monolithic application. But, as with any tool that's as feature-rich as JBoss, there are number of pitfalls and complexities, too.

Most developers struggle with the same issues...

©2019 LearnIT (support@pdfchm.net) - Privacy Policy