Day 2

Day 2 started with a very brief meeting where we went over the schedule for the next six weeks. Abstract, outline, presentation; two weeks per task. It was at this point that I realized the difficulty of making technical topics sound interesting, then I immediately dismissed the problem as one for my future self. Today was dedicated to Support Vector Machine (SVM) creation, evaluation, and optimization. I was unaware of many of the wonderful functions included in the provided libraries, and ended up doing the data reformatting less elegantly. It still worked, so I left it. When I finished up my SVM code, I tried to help Nate with the errors he was running into. The keyword here is "tried." Note that it's not easy to explain concepts that you figured out hours earlier and happen to be more complicated than they should be. Nate was a good sport about it though, and with Ron's help, he had a good idea of the solution by the end of the day. For the last part of the day, I built some autoencoders using keras and read some Stanford Deep Learning Tutorials. Making and testing the autoencoders was really satisfying, since the tutorial had plenty of code snippets to copy, keras was pretty easy to use, and the end results were good. The readings provided a comprehensive overview of deep learning concepts, but a ton of it went over my head. I'm going to have to finish up my autoencoder work and re-read some of those passages next time.

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