machine learning deep learning 21 January 2017

Geilo Winter School

Machine Learning, Deep Learning and Data Analytics

Recently (January 15-20 2017) I attended the 17th Geilo Winter School in eScience organized by SINTEF in the beautiful ski resort of Geilo; roughly midway between Oslo and Bergen. The winter school has quite a long tradition and throughout the years featured an impressive range of topics related to computer science, mathematical modelling, visualization and more. There is a full list of previous schools detailing their topics for those interested.

This year's topic was Machine Learning, Deep Learning and Data Analytics and once I heard about it I couldn't let such an opportunity pass by. For a long time I've been fascinated by artificial intelligence concepts from a philosophical point of view but more importantly I was curious about the practical methods and techniques that I could integrate into my work.

The program covered a broad range of academically and industrially relevant endeavors related to machine learning, deep learning, natural language processing, statistics, big data, and image processing. One of the talks that I really enjoyed was given by Mark Tibbetts on Industrial use-cases and work flows for ML where he showed how machine learning is applied to solve large scale industrial problems and gave us a glimpse on the difference between using ML in an academic vs industrial setting.

From an organizational point of view a thing that deserves to be mentioned was the schedule which was neatly arranged to integrate a couple of hours of free time before lunch to either have fun on the slopes or explore the various spa treatments at the hotel.

It was truly one of the best schools I attended so far. I had a great time listening to the lectures, learning, socializing, snowboarding and discussing about machine learning with people from various backgrounds since as it turned out I was the only chemist around.