2050, Paris n'est plus qu'un torrent de violences, le terrain de jeu de fanatiques déchus. L'air n'est plus respirable. Les hologrammes ont remplacé les hommes. Le travail n'est plus que le privilège de quelques-uns. Sous l'hégémonie de Dame Consommation, il est devenu interdit de fabriquer et réparer.
Ce livre est un signal d'alerte. Il est futuriste sans être fantaisiste. Un livre terrifiant de vérités aux premières pages et saisissant d'espoir aux dernières. Un très beau roman d'anticipation, empli d'humanité. Un bel appel au vivre ensemble et au retour à l'autosuffisance.
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.
Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.
- Use graphics to describe data with one, two, or dozens of variables
- Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments
- Mine data with computationally intensive methods such as simulation and clustering
- Make your conclusions understandable through reports, dashboards, and other metrics programs
- Understand financial calculations, including the time-value of money
- Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations
- Become familiar with different open source programming environments for data analysis
"Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla
"An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora
Philipp K. Janert was born and raised in Germany. He obtained a
Ph. D. in Theoretical Physics from the University of Washington in 1997
and has been working in the tech industry since, including four years
at Amazon.com, where he initiated and led several projects to improve
Amazon's order fulfillment process. He is the author of two books on
data analysis, including the best-selling "Data Analysis with Open
Source Tools" (O'Reilly, 2010), and his writings have appeared on
Perl.com, IBM developerWorks, IEEE Software, and in the Linux
Magazine. He has contributed to CPAN and other open-source
projects. He lives in the Pacific Northwest.