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Machine learning = a journey to deep learning : with exercises and answers /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Machine learning/ Andreas Wichert, Luis Sa-Couto.
其他題名:
a journey to deep learning : with exercises and answers /
作者:
Wichert, Andrzej.
其他作者:
Sa-couto, Luis.
出版者:
Singapore :World Scientific, : c2021.,
面頁冊數:
1 online resource (xvi, 624 p.)
標題:
Machine learning. -
電子資源:
https://www.worldscientific.com/worldscibooks/10.1142/12201#t=toc
ISBN:
9789811234064
Machine learning = a journey to deep learning : with exercises and answers /
Wichert, Andrzej.
Machine learning
a journey to deep learning : with exercises and answers /[electronic resource] :Andreas Wichert, Luis Sa-Couto. - Singapore :World Scientific,c2021. - 1 online resource (xvi, 624 p.)
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.
ISBN: 9789811234064Subjects--Topical Terms:
561253
Machine learning.
LC Class. No.: Q325.5 / .W53 2021
Dewey Class. No.: 006.31
Machine learning = a journey to deep learning : with exercises and answers /
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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.
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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"--Publisher's website.
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https://www.worldscientific.com/worldscibooks/10.1142/12201#t=toc
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