Previous Seminars

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Machine Learning with IBM Seminar

More than 90 delegates attended the Data Science Institute's last Advanced Data Analytics Seminar of the academic year. Dr Ed Pyzer-Knapp from IBM Research UK discussed the recent developments made by

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VOSON Lab Overview & Researching Politically-oriented Conversations on Twitter

On 3rd July 2017, the Data Science Institute welcomed Associate Professor Robert Ackland from the Australian National University. Professor Ackland gave an excellent presentation entitled 'VOSON Lab O

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Network Science For Online Social Media: An X-Ray or a Stethoscope For Society?

On 21st March 2017, the Data Science Institute welcomed Dr Mariano Beguerisse from the University of Oxford to present 'Network science for online social media: an x-ray or a stethoscope for society?'. Dr Beguerisse discussed the abundance of data from social media outlets such as Twitter, and the…

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Large Scale Analysis of Media Content (Twitter, News & Historical Newspapers)

Prof Nello Cristianini from the University of Bristol presented an excellent seminar on 'Large Scale Analysis of Media Content (Twitter, News and Historical Newspapers)'.Nello presented recent work in the area of media content analysis, its big-data origins, and its applications to social science…

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Google's Tensorflow: Not Just for Deep Learning?

More than 65 attendees from across the University came along to the seminar entitled 'Google's TensorFlow: not just for Deep Learning?' by the University of Lancaster's Dr James Hensman.​In this talk, James introduced Google's TensorFlow framework, and described how it can be used to build…

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The Zig-Zag process & Super-efficient Sampling For Bayesian Analysis Of Big Data

Standard MCMC methods can scale poorly to big data settings due to the need to evaluate the likelihood at each iteration. There have been a number of approximate MCMC algorithms that use sub-sampling

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