Website | @RainyData
Alice is the Director of Data Science at GraphLab, a Seattle-based startup that offers powerful large-scale machine learning and graph analytics tools. She loves playing with data and enabling others to play with data. She is a tool builder and an expert in Machine Learning algorithms. Her research spans software diagnosis, computer network security, and social network analysis. Prior to joining GraphLab, she was a researcher at Microsoft Research, Redmond. She holds Ph.D. and B.A. degrees in Computer Science, and a B.A. in Mathematics, all from U.C. Berkeley.
9:00am–5:00pm Wednesday, 10/15/2014
Hardcore Data Science
Location: 1 E14/1 E15
Ben Lorica (O'Reilly),
Ted Dunning (MapR),
Tim Kraska (Brown University),
Alice Zheng (Amazon),
Anna Gilbert (University of Michigan),
Jon Kleinberg (Cornell University),
Kira Radinsky (eBay | Technion),
Rob Fergus (New York University and Facebook),
Ben Recht (University of California, Berkeley),
Brian Whitman (Spotify),
Hanna Wallach (Microsoft Research NYC & University of Massachusetts Amherst),
Dafna Shahaf (The Hebrew University of Jerusalem)
All-Day: Strata's regular data science track has great talks with real world experience from leading edge speakers. But we didn't just stop there—we added the Hardcore Data Science day to give you a chance to go even deeper. The Hardcore day will add new techniques and technologies to your data science toolbox, shared by leading data science practitioners from startups, industry, consulting...
10:00am–10:30am Wednesday, 10/15/2014
Hardcore Data Science
Location: E14 / E15
As humans, we want to understand the rationale behind data analysis models, which can often be conceptually challenging. In this session, we dive into common data operations and analysis methods to develop deeper knowledge of feature spaces and models. We take the perspective of how data appears to machines, in order to become more effective at using machines to model and analyze data.
1:30pm–5:00pm Wednesday, 10/15/2014
Location: 1 C03/1 C04
This tutorial focuses on hands-on data science skills from prototyping to production. Using GraphLab tools, we walk through multiple case studies such as fraud detection, social network analysis, and building personalized recommendation services.