In a blog post recapping his bootcamp final project, Metis graduate Matt Ahlborg introduces the topic by writing: "In the decade since the Satoshi white paper was published, we can now say that the word Bitcoin has entered global consciousness. However, many people, including some very intelligent and well-respected people in their own right, still have trouble understanding the idea of Bitcoin and in many cases even question its value and purported utility in the world."
He continues: "While Bitcoin today showcases a vast body of anecdotal evidence which argues its utility or potential future utility, due to the pseudonymous nature of the blockchain as well as other factors, it is still hard to come across aggregate data which shows this behavior occurring on a consistent and measurable scale. To attempt to address this problem, I took a close look at trading volumes on the Peer-to-Peer Bitcoin trading website Localbitcoins.com."
"Magazine covers have an underrated influence on our culture," writes Metis graduate Nora G. May in a blog post about her bootcamp final project. "Even if you don’t read tabloids or women’s magazines, you can picture a Cosmo or People magazine cover and can give examples of the types of stories they run. Every time you’ve purchased groceries or gotten a snack for the plane, you see these magazines and they make an impression," she continues.
In an attempt to understand the market appeal of magazines, specifically women’s magazines, May used data analytical tools to abstract magazines' marketing techniques. She extracted the text from magazine covers, performed NLP topic modeling, and used image processing techniques to understand graphic trends and representation.
I came across a question on Quora that boiled down to: "How can I learn machine learning in six months?" I started to write up a short answer, but it quickly snowballed into a huge discussion of the pedagogical approach I used and how I made the transition from physics nerd to physics-nerd-with-machine-learning-in-his-toolbelt to data scientist. Here's a roadmap highlighting major points along the way.