Danny Lange presents Uber’s Machine Learning service that can perform functions such as ETA, fraud detection, churn prediction, forecasting demand, and much more.
Pushpraj Shukla discusses how Microsoft Bing predicts the future based on aggregate human behavior using one of the largest scale data sets, and recent progress in large scale deep learnt models.
William Markito Oliveira and Fred Melo discuss the architecture and implementation details of a stock prediction solution built entirely on top of open source code and some R and a web interface.
Claudia Perlich keynotes on M6D’s approach to Big Data, using data granularity to build predictive models used for user targeting, bid optimization and fraud detection.
Neal Gafter reviews the long history of Java from its inception to the present and makes an incursion into what he thinks will be a great future and guessing what might come in Java SE 9+ after 2014.