Data Science Seminar: Machine Learning

On November 23 the Institute of Computer Science kicks off a brand new series of seminars on data science which aim to connect scientists and applied approaches from the industry.

The first seminar in the series will focus on machine learning and will feature academic speakers from the institute as well as representatives from companies. There will be short presentations by the speakers, followed by a panel discussion. Questions and contributions are of course very welcome.

So what to expect from the seminar on machine learning?

When faced with high-dimensional, large scale data generated from everyday company operations, it is not clear how to extract value from them. Machine learning tools are powerful out-of-the-box solutions for this scenario. They enable visualising complex data in simpler forms, finding regularities, learning class structure, and forming predictions about future. In this meetup, our speakers will show off how they have used them in new models, applied them to answer interesting questions from real life data, and developed theory to understand their performance.

Everyone who cares about understanding large scale data is welcome.

The event will take place on November 23 in the atrium of Paabel (Ülikooli 17) from 17.00-20.00.

Speakers and the agenda:

17.00 Gathering
17.20 Introduction by Leopold Parts, Senior Research Fellow in Bioinformatics & Group Leader at Wellcome Trust Sanger Institute
17.30 Raul Vicente, Professor of Data Science, UT Institute of Computer Science
17.45 Andres Kull, Product Analyst at Pipedrive, advisor of machine learning at VitalFields
18.00 Vladimir Šor, CTO at Plumbr
18.15 Mark Fišel, Associate Professor in Language Technology, UT Institute of Computer Science
18.30 Taavi Tammiste, Head of Data Science at Mooncascade
18.45 Amnir Hadachi, Lecturer of Distributed Systems, UT Institute of Computer Science
19.00 Panel Discussion, moderated by Leopold Parts