Image Processing: The Simple and The Complex

We've seen in the past several blog posts on how you can learn simple image classifiers with BigML, via the interface, the API, and with the BigML Python Bindings, and we've also seen that you can train unsupervised models on the same images. But let's dig a little deeper and explore different approaches to an image processing problem. One of the things we try hard to do at BigML is, to paraphrase Alan Kay, make simple things simple and complex things possible. It's a relatively simple thing to train an image classifier: You have a bunch of images, those images have classes, and you want to train a model that will classify any new image into one of those classes. One great application of this is the area of security and monitoring: You have a system constantly looking at something and you want to be alerted when that thing changes.