For my summer internship, my project involves using machine learning to help small businesses with funding. I learned a lot about machine learning in the process, so I gave a talk about it to some of my co-workers and shared the slides online:
I also shared the code on my Github. The following is an essay version of the talk.
Before I say anything, I want to show you a video from the 2017 WWDC Apple conference, WWDC is the annual conference which Apple hosts and is one of the most important events in the tech calendar for showcasing the top technology applications that will be used in the near future.
Apple wants you to know that they're really focused on machine learning pic.twitter.com/ZCJvBPGQpi
— VICE News (@vicenews) June 6, 2017
So the machine learning supercut gives some context to how I think society generally views machine learning. On the one hand, it’s a technology which has a lot of potential and will drastically change aspects of our society. Conversely, because it has so much potential people have a tendency to over promise and over-advertise the things which machine learning is capable of doing and often turn it into a marketing gimmick and annoying buzzword. For a high level, non-technical summary of what machine learning is about and what the future of technology in general, I recommend Homo Sapiens by Yuval Noah Harari.
I take a more middle-ground approach and say that you should judge it on the merits of what you can actually build with machine learning, but first, you have to understand what machine learning is.
(Guage audience level) How many of you: has never coded before… used ML in a small side project … Studied ML at a Master’s or Ph.D. Level, written or helped write a paper about ML etc.)I’ve tried to structure my talk in such a way that non-technical people will find it interesting and the more technical, ML-experienced people may some new, interesting concepts.
The reason my talk is called practical machine learning is because I consider myself a very pragmatic, practical person and whenever I learn something, the first thing I ask myself is how can I apply what I’ve learned and put it into practice. Hopefully, after today’s talk, you will hopefully be able to apply what you’ve learned and build actual ML projects. Alright, so let’s get started
My talk was greatly inspired by 2 tutorials which I did, the website is awesome and the guy who runs it Harrison Kinley is a very good teacher.
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