Sprache: Englisch
Verlag: Packt Publishing, Limited, 2022
ISBN 10: 1803242388 ISBN 13: 9781803242385
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Sprache: Englisch
Verlag: Packt Publishing 10/31/2022, 2022
ISBN 10: 1803242388 ISBN 13: 9781803242385
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Paperback or Softback. Zustand: New. Machine Learning Techniques for Text: Apply modern techniques with Python for text processing, dimensionality reduction, classification, and evaluatio. Book.
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Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 620056843X ISBN 13: 9786200568434
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hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 620056843X ISBN 13: 9786200568434
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Sprache: Englisch
Verlag: Chapman and Hall/CRC 2013-12-11, 2013
ISBN 10: 1439857245 ISBN 13: 9781439857243
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Sprache: Englisch
Verlag: Elsevier Science & Technology, San Francisco, 2025
ISBN 10: 0443328188 ISBN 13: 9780443328183
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Paperback. Zustand: new. Paperback. Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Sprache: Englisch
Verlag: Elsevier Science Feb 2025, 2025
ISBN 10: 0443328188 ISBN 13: 9780443328183
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Taschenbuch. Zustand: Neu. Neuware - Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data.
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Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 620056843X ISBN 13: 9786200568434
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Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 620056843X ISBN 13: 9786200568434
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