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Djorgovski (2008) Machina Coelestis: Computationally Enabled, Data Intensive Astronomy for the 21st Century 1h 14m (Requires Internet Explorer)
VideoLectures.net: Currently about 100+ video lectures on the topic of data-mining, some of which are particularly relevant to astronomy. See in particular Aleksandar Lazarevic’s tutorial on Data-Mining for Anomoly Detection, and Gabriel Wachman’s Kernels for Periodic Time Series Arising in Astronomy.
AstronomyCast Episode 118: Sky Surveys (2008). From the show notes: “In the old days, astronomers had to beg for telescope time. They’d put together a proposal, convince observatories to gather data for them, crunch that data and release the results. No telescope, no results. But everything’s different now. Fleets of robotic telescopes constantly scan the skies, building up a vast database of raw data about the Universe. Anyone who wants can access the information through the Internet, download what they need to do real science. No telescope necessary. Let’s look at the development of sky surveys, and how they’re changing how astronomy gets done.”
Presentations & Tutorials
Sloan Digital Sky Survey Data Release 7 Tutorials: “These pages provide detailed worked examples of SDSS data retrieval using the various interfaces provided. In addition, we provide discussions of how to access and read some of the unusual file types used in the survey, and perform certain operations, such as calibration.”
ADASS XX, Boston MA, USA November 7-11, 2010: Provides a forum for scientists and developers concerned with algorithms, software and software systems employed in the acquisition, reduction, analysis, and dissemination of astronomical data. The program will include invited talks, contributed oral and display papers, tutorials user group meetings and special interest group meetings (called BOFs).
KDD-2010, Washington D.C., USA (July 25-28, 2010)
Astroinformatics2010, Pasadena CA, June 16-19, 2010
[Conference archives contain video and pdf-formatted slides from each session. See the conference agenda as a cross-reference.]
dotAstronomy / Astronomy and the new media, Cardiff University UK, September 22-24, 2008. [Contains a number of video presentations specifically relevant to data-mining astronomical data.]
Machine Learning, Andrew Ng, Stanford University, 20 Tracks (Requires iTunes)