Practical Deep Learning

FOREWORD

Since the dawn of the modern digital era, scientists and engineers have taken inspiration from the human brain to imagine how massively parallel networks of simple neuron-like processors might learn and adapt from experience. There have been waves of excitement in this topic as new mathematical methods were developed. In 1958, Frank Rosenblatt proposed a learning device called the Perceptron, which had the amazing property that it could learn any task that one could program it by hand to perform. The enthusiasm for this device vanished when Marvin Minsky and Seymour Papert performed a careful analysis showing limitations on what the device could be programmed to do, both in principle and in practice.

In the late 1980s, cognitive scientist ...