Daniel Tunkelang focuses on the data science mindset for successfully applying machine learning to solve problems: express, explain, experiment.
Bryan Nehl makes an introduction to the data science: data formats, ETL tools, NoSQL databases, languages, libraries, techniques and approaches for exploring data and extracting value from it.
Justin Moore shares how Facebook's own advances in Data Science have solved intricate location technology problems and how these lessons can be applied to other verticals to achieve similar gains.
Tomas Petricek introduces F#’s capabilities in dealing with scientific data: type providers -CSV, XML, JSON, REST-, interactive development, data visualization libraries, integration with R or MathLab
Gloria Lau describes some of the products built for the higher education sector, the data standardization process, determining school similarity and identifying notable alumni.