Last Wednesday, akquinet tech@spree had the pleasure to host a technology evening of the Software Initiative Berlin Brandenburg (SIBB). The event was devoted to all things data and machine learning and comprised two talks, plus plenty of discussions (and pizza) afterwards.
The first of the talks was given by me and was intended as a general initiation into the topic. I thought it might be nice to post the slides, so they are now up on SlideShare:
I started by giving an overview of the different kinds of data analytics, and then focussed on predictive modelling and machine learning in particular. After introducing the main ideas, I walked through the practical steps that go into a data science project: from formulating the problem and getting to know the data, to data cleaning and feature engineering, to modelling and model validation.
The second talk of the night was by Boris Bugarski from Microsoft, who did a great job of explaining the capabilities of Azure when it comes to data analytics and showed an interesting demo of image recognition for Yorkshire terriers.
A big thank you to the organizers and to everyone who came – it was a great evening!