High Performance Deep Learning, Part 1 - KDnuggets


Machine Learning is being used in countless applications today. It is a natural fit in domains where there is no single algorithm that works perfectly, and there is a large amount of unseen data that the algorithm needs to do a good job predicting the right output. Unlike traditional algorithm problems where we expect exact optimal answers, machine learning applications can tolerate approximate answers. Deep Learning with neural networks has been the dominant methodology of training new machine learning models for the past decade. Its rise to prominence is often attributed to the ImageNet [1] competition in 2012.

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