Landmine or Coke Can: Deep Learning with GPR Data

Time Slices5_Grid9One of the projects that has taken up a lot of my time the past few months is that of a UAV (drone) based Ground Penetrating Radar (GPR) system. There are a number of applications for this but the one we have been focussing on initially is landmine and UXO clearance. The elements that make up such a system are quite broad. Ranging from sensor design, UAV integration, positioning, terrain following to data analysis. As with many drone projects most of the attention tends to go to the hardware and the flying. While that is certainly important and I have been working on those elements too, the whole system is only as good as the quality and interpretability of the data you get back. That is key. With this post I’ll aim to give a brief summary of the work I have been leading on this front.

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MSF Canada Drone Day

DSC00266I recently had the honour of attending the MSF Canada AGM in Montreal to join Ivan Gayton and Stephen Mather (from Open DroneMap fame) run a drone day for the MSF logisticians. The aim being to show the realm of the possible with current drone technology as well as touch on future trends and ethical considerations.

A second agenda we had was to promote the democratisation of drone technology to enable crowd sourced imagery collection as part of the Missing Maps initiative. 2015-06-12 14.57.27More specifically, the goal is to bring drone technology down to a level where it can be built, maintained, and operated safely, responsibly, and independently by a local high school in South Sudan, the local University of Lubumbashi, or similar. 

The full (draft) concept note behind this can be found here.

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Where are the engineering hipsters?

enghipsterIts late and I’m on my way back from the final demo evening of the Advanced Skills Initiative (ASI). The ASI programme takes disgruntled academics and puts them through an intensive 8 week data science course so they can move into the bustling data science job market. I was a mentor on the machine learning front and it was great to see the fellows evolve and battle through their projects.

One thing struck me though. Something that has been bugging me for a while. Projects pitched at events and meetups like this invariably cover product recommendation, preference learning, financial NLP, churn prediction, adclick prediction, social media trending analysis, etc.

As somebody who likes tangible things, I can’t help but wonder. Where are the projects & startups from aerospace, automotive, marine and other engineering disciplines? Why aren’t we seeing projects from Airbus on smart IVHM, from Jaguar on crumple zones, from Reaction Engines on engine performance, from ASV on marine autopilots, from Princess on vibration control, from McLaren on race strategy, from Dyson on path planning, etc. I personally find these things hugely interesting and fascinating topics. The possibilities for data science / machine learning are endless, prognostics being the obvious example.

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Data for Good ?

pydatameetup

A short post to share the slides I used during my talk at the 4th PyData London Meetup. Organized by Ian Oszvald, co-Taarifian Florian Rathgeber, and others, its always a full house with a friendly crowd.

Given the limited time I had to put something together I think the talk was well received and triggered lots of good feedback and conversations in the pub afterwards. Hopefully I managed to ‘turn’ a few attendees 🙂

Aside: There has been a lot happening on my end the last couple months and its been tough (but exciting!) keeping up with it all. My digital prescense has been lagging behind somewhat but slowly getting there.

–Dirk

 

Taarifa Hackathons: Boston, London, Dar Es Salaam

taarifa_logoA lot has changed since I last blogged about Taarifa. We have been the recipient of a World Bank Innovation Fund grant and are going through the Geeks Without Bounds Humanitarian Accelerator. Work is really kicking off in earnest now and if you follow the project you will see much happening over the next two months.

In order to improve the platform and grow the community we are running a number hackathons around the world. You are hereby cordially invited to come hack on data, software (front and back end), hardware, and all the bits between in

The Challenge

There’s not much in the way of access to clean water in Tanzania. In the informal settlements, there are a bunch of water points, but many of them are broken. Rather than a continual process of putting in new ones, the local water engineers want to fix the existing ones – but they don’t know where the broken points are. This also prevents large-scale response organizations from accurately deploying resources (and seeing what initiatives are already working).

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Introduction to Machine Learning and scikit-learn: 1 Day & 5 Day Course

classification

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.

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