Anbieter: HPB-Red, Dallas, TX, USA
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!
Zustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 92,89
Anzahl: 12 verfügbar
In den WarenkorbZustand: New.
Zustand: As New. Unread book in perfect condition.
Anbieter: ALLBOOKS1, Direk, SA, Australien
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 107,66
Anzahl: 1 verfügbar
In den WarenkorbZustand: New. In.
Verlag: Chapman and Hall/CRC 2019-11-21, 2019
ISBN 10: 1138495689 ISBN 13: 9781138495685
Sprache: Englisch
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
EUR 105,25
Anzahl: 1 verfügbar
In den WarenkorbHardcover. Zustand: New.
EUR 115,95
Anzahl: 3 verfügbar
In den WarenkorbZustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 108,89
Anzahl: 12 verfügbar
In den WarenkorbZustand: As New. Unread book in perfect condition.
Zustand: New.
Zustand: New.
Verlag: Taylor and Francis Ltd, GB, 2019
ISBN 10: 1138495689 ISBN 13: 9781138495685
Sprache: Englisch
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich
EUR 161,36
Anzahl: 1 verfügbar
In den WarenkorbHardback. Zustand: New. Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results.Features:· Offers a practical and applied introduction to the most popular machine learning methods.· Topics covered include feature engineering, resampling, deep learning and more.· Uses a hands-on approach and real world data.
Zustand: New.
EUR 163,45
Anzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 459 pages. 9.25x6.25x1.00 inches. In Stock.
Verlag: Taylor and Francis Ltd, GB, 2019
ISBN 10: 1138495689 ISBN 13: 9781138495685
Sprache: Englisch
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
EUR 152,42
Anzahl: 1 verfügbar
In den WarenkorbHardback. Zustand: New. Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results.Features:· Offers a practical and applied introduction to the most popular machine learning methods.· Topics covered include feature engineering, resampling, deep learning and more.· Uses a hands-on approach and real world data.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 129,89
Anzahl: 1 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 459 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand.