Recursive Cartography: First Steps with TensorFlow and Deep Learning

The most promising aspect of Deep Learning for me is the possibility of removing many of the "magic touch of the analyst" steps of feature extraction, model selection, manual data transformations, etc. that make machine learning models traditionally difficult to generalize. I tried to take a small step towards improvements of this process with my dissertation research by finding features that would generalize between scenes and using those to automatically classify urban areas in images. I used those cross-scene features to provide labels for spectra extracted through an unsupervised process. I'm struck by the fact that deep learning tasks in image recognition take this process back one step further and provide a means to learn those features at multiple orders and levels of abstraction. To see what I'm referring to, see some of the papers on deep convolutional networks, for example: