Workshop 13. februar i Ålesund AI workshop – from hype to real-world applications

In this workshop, Vegard Flovik from Axbit will explain what Machine Learning is all about, and how you can actually apply it in your business and projects. Then it is your turn to get your hands dirty with Machine Learning in practice, guided by Vegard.

Kelvin Sundli

arrangeres av Kelvin Sundli og resten av fagfolkene fra faggruppen AI and Robotics

Medlempris: 0.00 Ordinær pris: 0.00 Meld på

Link to streaming

This event is a cooperation between Den norske dataforening (AI and Robotics), Tekna Big Data/Ålesund avdeling and IEEE.

Bring your own PC and work hands-on with Machine Learning

With Vegard Flovik, Lead Data Scientist, Axbit AS

17:00–17:45: Machine Learning introduction
17:45–18:00: Break
18:00–19:00: Hands-on Machine Learning (You may stay longer than 19:00, if needed)

Requirements: You must bring your own PC and have a Google account. You should have basic programming knowledge. Familiarity with Python and Jupyter Notebook is useful, but not required.

We will serve baguettes from 16:15 (4:15 PM).

This event is organized by IEEE, Den norske dataforening and Tekna Big Data / Ålesund avdeling.
The workshop is held in English. The workshop and the streaming are free and open for everyone.

Follow this link (to be published later) to watch the Machine Learning introduction live 17:00–17:45.
You do not need to – and should not – sign up if you only are watching the streaming.

Vegard Flovik, PhD, works as a Lead Data Scientists at Axbit, where he creates solutions within advanced analytics and Machine Learning. Among his projects is CreateView using computer vision to detect lice on fish in fish farms. He has also applied Machine Learning to improve the analysis of spectroscopy data from marine products. Previously he worked as a Principal Data Scientist at Kongsberg Digital and as a researcher at NMBU. Vegard also writes articles on AI and its risks, gaining worldwide attention and appreciation. Among his articles; how to teach AI physics, and how to «build an AI that can read your mind».