Deep Learning, an introduction with two nice short examples

Beschreibung

This booklet introduces the most important basics of deep learning. It describes the very frequently used method of how a computer can learn using neural networks and training data and apply what it has learned to other questions similar to the training data. Two simple about 'one-pager' examples in Python show how training a neural network with forward and back propagation works and how the trained system can process simple forms of artificial thinking. The two short Python programs "Learning truth tables" and "Recognizing a questionnaire" are printed in full and are easy to follow.

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Roland Büchi

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Artificial Intelligence Machine Learning deep learning Back Propagation Python

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