Day 5

I began the first experiment of my project today. But first, I prepared by doing some reading on the topic of hyperspectral image classification. I read a paper written by Ron and Dr. Kanan about self-taught feature learning. It discussed two self-taught learning frameworks: the multiscale ICA and the stacked convolutional autoencoder. Much of it was difficult for me to understand because I am new to this topic, but I learned more about self-taught machine learning programs. After I finished reading, I began my first experiment. The first step was to document already written machine learning code and to figure out what that code was doing. I read about the standard Python documentation style, then I began to document the code. This proved to be challenging, because this code implemented many methods from outside of itself, which meant I had to understand those methods as well. Today I learned that understanding and following code that was written by someone else can be just as challenging as writing code myself.

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