Article
Way back in the late 1920s John Von Neumann established the main problem in game theory that has remained relevant still today: Players s1, s2, ..., sn are playing a given game G. Which moves should player sm play to achieve the best possible outcome? Shortly after, problems of this kind...
Mina Krivokuća
Developing symbols which have some value is a trait unique to humans. Recognizing these symbols and understanding the letters on an image is absolutely normal for us. We never really grasp letters like computers do, we completely base our ability to read them on our sight. On the other hand,...
David Landup
Transfer learning is a powerful technique for training deep neural networks that allows one to take knowledge learned about one deep learning problem and apply it to a different, yet similar learning problem. Using transfer learning can dramatically speed up the rate of deployment for an app you are designing,...
Dan Nelson
Genetic algorithms are a part of a family of algorithms for global optimization called Evolutionary Computation, which is comprised of artificial intelligence metaheuristics with randomization inspired by biology. Wow, words can really be arranged in any order! But hang in there, we'll break this down: Global optimization is a branch...
Darinka Zobenica
There is no doubt that neural networks, and machine learning in general, has been one of the hottest topics in tech the past few years or so. It's easy to see why with all of the really interesting use-cases they solve, like voice recognition, image recognition, or even music composition....
Scott Robinson
Over the last few years especially, neural networks (NNs) have really taken off as a practical and efficient way of solving problems that can't be easily solved by an algorithm, like face detection, voice recognition, and medical diagnosis. This is largely thanks to recent discoveries on how to better train...
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