It's been an interesting conference, and I learned quite a bit. Things I learned:
- I got some insight as to how R works - it's a different paradigm than languages I'm used to.
- I know more about data science than I thought.
- I know far less about data science than many other people.
- Which ML approaches are valid for which questions you're trying to answer.
- There are a whole bunch of nifty technologies out there that I need to explore.
- There are a whole bunch of nifty companies out there using big data that I need to learn about.
- Julia is the name of a programming language. :)
The conference didn't push me that much, interestingly. I'm not exhausted or brain-dead the way I thought I would be. That may be due to actually getting enough sleep before each day (with one exception) but I think it was really just a process of putting together pieces of things that I've been learning for the last few months.
There's a whole bunch of techniques that I now understand how to use on my Kaggle data. Some of the things that I've thought about Hadoop and the surrounding architectures turned out to be validated by some clearly very smart people. That gives me confidence in the way I approach problems.
In summary, the conference gave me a perspective on where I fit within the data science community at large, and the feeling that I'm on the right track with my experiments and research.
From here, I plan to spend some time messing with various ML techniques and getting down and dirty with some more statistics. From there, maybe I can find and join a data science team that needs a good developer?
Forward the data science!
... but home first.
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