I’m a software developer currently located in Calgary, AB, Canada (although I’m originally from the Northwest US). I work for a startup focused on managing cameras at industrial sites. We use computer vision to augment imagery with metadata about the contents of the images, making the images indexable and actionable by machines. I mostly focus on general web development (we have a few purely CV focused devs) but would like to have a stronger grasp of what’s going on in our tooling and how to contribute to future development. This course really appeals to me in its “get shit done” nature, I’m pretty comfortable with Python and AWS and would prefer to start building things and then get into the mathematical background as I go along (this was the general approach I took to learning software development, build and learn along the way).
Aside from my day job, my background is in spatial data and I typically focus on geo-stuff when working on side projects. I’m surprised by the lack of machine learning in that arena (maybe I’m just not exposed?). My goal for this course is to have enough of a grasp of the current state of ML to be able to know where I want to focus my efforts and research. Currently it all feels very abstract, making it difficult to even know what problems I could be solving and where to turn next.
In my spare time, I am spending time with my 8 month old daughter (fatherhood is still a very new world for me), cooking, and building small web apps and IoT gadgets for my house.
@robin Cool to see that you’re from Planet Labs. I saw Frank Warmerdam do a presentation about PL at FOSS4G a few years ago and have been really interested in your company ever since. Looking forward to seeing what kind of services your team develops!