Assume you want to maintain constant pressure in a certain container. You have control of a valve that can pump more air into it, or release some air. It sounds like a simple task: if the pressure is below the target pump some more air in, and if it's above the target, release some -- that should do it. Months pass, and your valve accumulates wear and tear: but you notice nothing, because your controller is doing its job, keeping the pressure constant -- even if that means pumping a little more air each week to offset a small leak in the connection between the valve and the container.
FILE - In this May 13, 2015, file photo, Google's self-driving Lexus drives along a street during a demonstration at Google campus in Mountain View, Calif. While the Boston region is a center for robotics and artificial intelligence research, none of the Northeast states allows self-driving cars to be driven or tested on public roads. But Massachusetts officials are looking in 2016 at turning part of the former Devens military base into a self-driving testing ground.
Almost a year ago QuantStart discussed deep learning and introduced the Theano library via a logistic regression example. Given the recent results of the QuantStart 2017 Content Survey it was decided that an up to date beginner-friendly article was needed to introduce deep learning from first principles.
Without loads of data, we have problems that not even the most intelligent machine learning systems can solve. Simple directions become extremely difficult without a destination. Navigating and processing a healthcare claim is impossible without a payer identified. Finding the best vet for a pet is difficult without knowing the species.