My co-organizer Ben Recht and I are proud to announce the return of Hardcore Data Science day to Strata+Hadoop World in California. We have outstanding speakers – 11 talks in total – and I expect the track to sell out (as it has done in the past).
- Deep Learning enthusiasts will enjoy sessions on its application to speech (Tara Sainath) and vision (Fei-Fei Li)
- One the most eminent researchers in machine learning, Michael Jordan, is giving a talk on statistical decision theory & big data. He recently participated in a reddit (Ask Me Anything) session and was profiled by IEEE Spectrum (his reaction to that piece is here).
- Machine-learning: Maya Gupta of Google is giving a talk on interpretable & robust models, Anima Anandkumar (of UC Irvine) will discuss the use of tensors for ML, and John Canny (of UC Berkley) will describe the new BIDMach toolkit.
- Applications: David Andrzejewski (of SumoLogic) will examine the use of Graph Mining techniques for machine data, Eamonn Keogh (of UC Riverside) will survey methods for mining large-scale time-series, and Chris Re (of Stanford) will talk about recent applications of the DeepDive knowledge base framework.
- John Myles White will explain why data scientists should consider the Julia programming language, and Alyosha Efros will outline recent progress in Visual Data Mining techniques.