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Machine learning [electronic resource] : a journey to deep learning : with exercises and answers / by Andreas Wichert, Luis Sa-Couto.

By: Wichert, Andrzej.
Contributor(s): Sa-couto, Luis.
Material type: materialTypeLabelBookPublisher: Singapore : World Scientific, 2021Description: 1 online resource (xvi, 624 p.).ISBN: 9789811234064.Subject(s): Machine learningGenre/Form: Electronic books.DDC classification: 006.31 Online resources: Access to full text is restricted to subscribers.
Contents:
Preface -- Introduction -- Probability and information -- Linear algebra and optimization -- Linear and nonlinear regression -- Perceptron -- Multilayer perceptron -- Learning theory -- Model selection -- Clustering -- Radial basis networks -- Support vector machines -- Deep learning -- Convolutional networks -- Recurrent networks -- Autoencoders -- Epilogue -- Bibliography -- Index.
Summary: "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"--Publisher's website.
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Includes bibliographical references and index.

Preface -- Introduction -- Probability and information -- Linear algebra and optimization -- Linear and nonlinear regression -- Perceptron -- Multilayer perceptron -- Learning theory -- Model selection -- Clustering -- Radial basis networks -- Support vector machines -- Deep learning -- Convolutional networks -- Recurrent networks -- Autoencoders -- Epilogue -- Bibliography -- Index.

"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"--Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

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