Supervised Learning

I’m a mostly self-taught programmer/developer. I work as a data analyst and try to leverage my work for opportunities to learn new tools and tricks, but for the most part my learning has come by way of pet projects. I thought about starting this blog for some time before I actually started posting. Originally, I wanted to use it to log useful code snippets or elegant solutions I developed (primarily to problems at work). I generally don’t find I have the time to document that sort of thing while I’m working so although I’m only a few posts deep, I feel like this blog is going to be more of a project log.

Anyway, I didn’t start typing to produce a manifesto for my blog. I’m here to brag. Tonight was orientation for my grad program! That’s right, after years of committing most of my free time to teaching myself shit, I have finally re-entered academia. I am now a graduate candidate in the Georgetown University Mathematics and Statistics Program.

At the moment, I’m sufficiently interested in my work to to the  part time thing, which means one class this semester to get my feet wet, then two classes every other semester for a total of ten classes for the program. My first class is Probability with the book A Course in Probability. I think the program has a primarily frequentist slant, but I hope to supplement this with a Bayesian Statistics class next semester and I suspect at least one class from the comp sci department, either Artificial Intelligence or Machine Learning.

As a 27 year old I don’t think I’m old from the program, but now that I think about it I don’t remember seeing any faces in the room tonight that looked older than me, so maybe I am going to be the old man of the bunch.

In any event, I’m excited and it’s going to be fun. I’ve got my text book, but I’m also simultaneously enrolled in SEVEN coursera courses (I’m mainly signed up for access to the content, I suspect I won’t have the time to finish any of the within the due date. Maybe one. I’ll finish them on my own time, anyway), so I think I’ll use my free time for other learning fun while I can. During my mini freak-out about whether or not I’d learn some Bayesian analysis in this program I picked up the textbook Pattern Recognition and Machine Learning (yes, I read textbooks for fun. I’m that guy), so I’ll try to dig into that some more tonight.
Oh yeah: go Hoya’s.

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