Earlier this week, dozens of technologists from the Microsoft DX Team met in San Diego for a team hackathon.
Some brought projects they started back home; some brought hardware with them to control via Bluetooth or USB cable or through the Internet; some brought an idea for a software project; some for a hardware project.
I came with a desire to learn more about Azure Machine Learning. I was inspired by the work that my teammate Jennifer Marsman was doing analyzing EEG data with AML. (link)
I began by walking through a couple tutorials: here and here.
Then I tried it myself. AML provides some sample data sources, so I imported the xxx data. I cleaned the data and applied a Category algorithm.
Machine Learning seems complex and the AML tools are not all intuitive when you first begin working with them; but they are not difficult to master. And the graphical interface of ML Studio lowers the learning curve considerably.
I'll provide more details and instructions about this project in a future blog post.
For now, my message is that building something yourself is the best way to learn any technology. Pick a project, set aside some time, and build it. I know that not every company invests in a day of hacking like mine did, so many of you will need to invest your own time in order to get this benefit. But it’s worth it.
My project wasn't nearly as sexy as some created by my colleagues. But my knowledge of Machine Learning is an order of magnitude greater than it was a week ago.
My Machine Learning experiment