Update: These courses have now been taught successfully. If you are interested let me know.
Note: These were originally delivered through Persontyle, however I am no longer affiliated with them in any way after a very unprofessional experience.
I am happy to announce I will be teaching two Machine Learning courses over the summer: A one day high level overview of machine learning is all about and a longer 5 day introductory course that goes into more depth and includes lots of hands on labs with Python scikit-learn. See below for details.
Today I attended the CDAC Workshop Digital Humanitarian Response – What Should the Future Look Like?
Organised by Justine McKinnon from Standby Task Force and Jessica Roland from Translators Without Borders, it was attended by 25 odd (operational) people from various humanitarian organisations (MSF, Red Cross, World Vision, ACAPS, CDAC …) with among them quite a few familiar faces. The aim of the workshop was quite ambitious and the question was not fully answered but it triggered some good discussion and useful connections were made. (BTW: What will happen to all the post-its? They never got discussed !?)
I managed to scribble down some remarks that stuck with me and these are dumped below. Its only a small, random subset of what was talked about but generally very similar in content to the Rescue Global workshop I wrote about in my last post.
I recently attended a workshop with Rescue Global (RG) and this blog post captures some of the discussion and points that are interesting and useful to digital humanitarians like myself. The better we understand how disaster response works (or doesn’t work) the better we can build our tools and get them used in anger.
Given my activity in the general Tech4Good space and autonomous systems I could not let Patrick’s announcement slide without doing a little post here to help spread the word.
One of the projects I have been involved with recently was a collaboration with the Agents, Interaction, and Complexity group at University of Southampton. The same group who we are also involved with in the Orchid project. This particular project was on Measuring and Predicting Departures from Routine in Human Mobility, building on the PhD work by James McInerney (now at Princeton) and his paper Breaking the Habit.
It is well known that humans generally follow very regular and predicable mobility patterns, both spatially and temporally. Lots of work has looked at exploiting and predicting those patterns but much less so on looking specifically at departures from those regular patterns. What can we learn from those departures from routine? How predictable are they?
Update: Unfortunately I purposely withdrew from the DL meetup after a very unprofessional experience with the co-organisers Persontyle. I Instead I joined forces with the London Machine Learning Meetup.
It has been almost half a year since I announced I would take over the London Big-O Algorithms meetup and bring it back to life. 5 Months later I am very happy to say all has gone extremely well, interest and attendance far exceeding my expectations. We have had a great set of meetups so far and all speaker slots are booked until June with talks from Google, The founder of ZeroMQ, Microsoft Bing, and many others. Really nice to see there is strong interest in good, solid, technical content.
However, enough about Big-O. This post is to announce a new meetup group that I have been convinced into setting up. The Deep Learning London meetup. The aim of this group is to bring together people interested in the family of machine learning methods that are concerned with learning distributed, hierarchical (“deep”) representations. Neural Networks being the most popular implementation. Its an area I have been looking at for a while and will be getting into quite deeply over the next couple of months (no pun intended). The format will be based around guest speakers sharing new research ideas and applications covering a wide range of fields from computer vision and natural language processing to autonomous systems and prognostics.
Note we are not assuming deep learning is the be-all end-all silver bullet of machine learning and welcome critical thoughts and benchmarks.
Sound interesting? Get in touch!
Last week I attended the Autonomous Systems Showcase event at the University of Southampton. The focus of the event was to bring together industry, government and academia “to explore commercial and research opportunities to deliver the next generation of aerospace, marine, defence and other advanced systems technology to keep the UK at the forefront of these important industries“.
Minister of State for Universities and Science, David Willetts, delivered the opening keynote. Other speakers included Sir Brian Burridge, Vice President of Strategic Marketing at Finmeccanica UK, and Michael Pickwoad, Production Designer from Dr Who, who talked about his creative process and the relationship between science and fiction.
The event also included industry and university showcase stands with particular emphasis on the work Southampton has done, and is doing, around unmanned aerial vehicles and underwater devices.