Sign up to stay up to date.
Data science, a relatively new discipline, is a beautiful combination of technology, business and mathematics that increasingly impacts every facet of daily life. It has emerged as one of the most exciting fields in the recent times. It has had a huge effect on how we work, how we rest, how we play and even how we vote. Vast quantities of data are being generated from transactions, sensors, social networks, cellphones and other connected devices. Organizations from nonprofits to corporations see this data, and the science to leverage this data, as a key threat or enabler to generate new products and services.
In this talk, we’ll be sharing our experiences so far in building our first predictive engine at NativeX. A leader in monetization and user acquisition services for mobile and desktop apps, NativeX’s mission is to create value for the app ecosystem. This project’s goal is to achieve that mission by using data science to help mobile users find new apps they’re likely to be interested in.
In particular we present the stages we’ve gone through in this mobile app advertising case study along with some lessons learned on the way: starting with getting data science expertise; defining the problems to be solved; understanding and cleaning up data; data engineering; feature engineering; data modeling with R; and finally, deploying a solution, operationalizing, and measuring results.
Minnebar 8 (2013-04-06)