Hardcore Data Science NYC 2014
Push the envelope of data science by exploring emerging topics such as data management, machine learning, natural language processing, crowdsourcing, and algorithm design with this O’Reilly video collection—taken from the Hardcore Data Science sessions at Strata + Hadoop World 2014 in New York. This...
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| Idioma: | Inglés |
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O'Reilly Media, Inc
2015.
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| Edición: | 1st edition |
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629989906719 |
| Sumario: | Push the envelope of data science by exploring emerging topics such as data management, machine learning, natural language processing, crowdsourcing, and algorithm design with this O’Reilly video collection—taken from the Hardcore Data Science sessions at Strata + Hadoop World 2014 in New York. This video collection includes: Doing the Impossible (Almost) Ted Dunning, Chief Application Architect, MapR Technologies Computing quantities such as medians or the number of unique elements usually requires a lot of time, a lot of memory, or both. But not always. Ted describes how these algorithms can be much simpler, and shows you how to apply them to applications like anomaly detection. Tupleware: Redefining Modern Analytics Tim Kraska, Professor, Brown University Learn about Tupleware, a new system developed at Brown University specifically aimed at the challenges faced by the typical user. Tupleware automatically compiles analytical workflows into highly efficient distributed programs instead of interpreting the workflows at run-time. Data Science for Humans, Not Robots Alice Zheng, Director of Data Science, Dato Data is intended for human consumption, yet governed, analyzed, and processed by machines. In this session, you’ll take the perspective of how data appears to machines in order to become more effective at using machines to model and analyze data for people. Big Data: Efficient Collection and Processing Anna Gilbert, Professor, University of Michigan You could spend your time collecting a ton of data from scientific applications, but there are more efficient ways to answer questions of interest. In this session, you’ll learn how to acquire data in summarized or compressed measurements. Computational Problems in Managing Social Information Jon Kleinberg, Professor, Cornell University Social media networks aren’t just venues for people to come together; they’re also explicitly designed environments whose architectures serve to shape behavior. You’ll learn several computational challenges that illustrate this tension between organic interaction and algorithmic design. Small Data Problems Kira Radinsky, CTO, SalesPredict What if you don't have enough data and still want to make predictions? Small data brings a completely different set of problems than big data. Instead of dealing with scale and efficiency, the game here is to draw statistical significant results from very few noisy examples. Building and Deploying Large-scale Machine Learning ... |
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| Notas: | Title taken from thumbnail image on resource description page (Safari, viewed July 1, 2015) Selections from Strata + Hadoop World 2014. |
| Descripción Física: | 1 online resource (1 video file, approximately 5 hr., 8 min.) |
