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This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives - the statistical perspective, the artificial neural network perspective and the deep learning methodology.
The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.
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