Open Source AI Tools – we looked under the hood….

Blog published by CW (Cambridge Wireless), under Artificial Intelligence / Machine learning

In November CW delivered an informal meetup at The Bradfield Centre, kindly sponsored by Five AI and supported by 2 of our special interest groups: Opensource Software and Artificial Intelligence.

71 delegates attended, the majority armed with fully charged laptops ready to code along to the opening presentation, delivered by Cambridge University graduate Lars Mennen, Software Engineer, FiveAI (pictured below). SIG Champion Dave Roberts who recently started working for FiveAI kicked-off the evenings talks.

Lars, software engineer presenting at a CW event

Lars explored training neural networks using tensorflow using a real time coding scenario which delegates could follow on screen. This was unashamedly technical and afterwards, whilst enjoying some beer and pizza, we learnt it was not too dissimilar from a postgraduate Computer Science Lecture. I’m pleased to say we welcomed a few Cambridge University students who had never been to a CW event before so it was great to chat with new faces.

You can view Lars slides here.

The second session revealed some alternative opensource ai tools; presented by Phil and Mary-Ann Claridge of Mandrel Systems. Tools discussed included the likes of WekoBigML, H2O (slides are coming soon!) and Phil explained some business case examples of how such tools can benefit and grow confidence in clients perhaps not well versed in python. Mary-Ann, expertly demonstrated one of the tools with ease.    

Phil and Mary-Ann Claridge at CW Software event

The evening was rounded off with some well-earned pizza and beers (from Cambridge start-up company Jocks & Peers -  please visit their facebook page for more info.)

Here’s what Dr Steve Marsh from GeoSpock had to say about the event:

The speakers were able to very succinctly provide both a how-to-get-started guide to machine learning as well as an in-depth discussion around the underlying principles of deep neural networks. Great event.


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