Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
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paperback. Zustand: Very Good. Fast Shipping - Safe and Secure 7 days a week!
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In den WarenkorbPaperback. Zustand: Very Good. 012040530X. Softcover, from closed pharmaceutical company library. Light shelf wear, felt tip mark on page edge. 398 pages, index, refs, illustrated. Chapters on: Central Nervous System Diseases; Cardiovascular and Pulmonary Diseases; Cancer and Infectious Diseases; Immunology, Endocrinology and Metabolic Diseases; Topics in Biology; Topics in Drug Design and Discovery; Trends and Perspectives. Contents are clean, tight and bright. Book.
Sprache: Englisch
Verlag: CreateSpace Independent Publishing Platform, 2013
ISBN 10: 1490908951 ISBN 13: 9781490908953
Anbieter: Sigrun Wuertele buchgenie_de, Altenburg, Deutschland
Zustand: Sehr gut - gebraucht. Hagmann, Jean-Philippe (illustrator). Broschiert Sehr guter Zustand, ohne Namenseintrag Zustand: 2, Sehr gut - gebraucht, Broschiert CreateSpace Independent Publishing Platform , 2013 , Simplicity for business success. Strategies for simple products, services and processes, Jiri Scherer, Michael Hartschen, Chris Bruegger.
Zustand: As New. Unread book in perfect condition.
Zustand: New.
Zustand: new.
Zustand: New. Second Edition 2024 NO-PA16APR2015-KAP.
paperback. Zustand: As New.
Zustand: New. 1st edition NO-PA16APR2015-KAP.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2024
ISBN 10: 3031570642 ISBN 13: 9783031570643
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 2nd edition. 185 pages. 9.44x6.61x9.69 inches. In Stock.
Sprache: Englisch
Verlag: CreateSpace Independent Publishing Platform, 2013
ISBN 10: 1490908951 ISBN 13: 9781490908953
Anbieter: California Books, Miami, FL, USA
Zustand: New. Hagmann, Jean-Philippe (illustrator). Print on Demand.
Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Switzerland|Morgan & Claypool Publishers|Springer, 2024
ISBN 10: 3031570642 ISBN 13: 9783031570643
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In den WarenkorbGebunden. Zustand: New.
Sprache: Englisch
Verlag: Springer Nature Switzerland, 2024
ISBN 10: 3031570642 ISBN 13: 9783031570643
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science. The authors present problems of validity, reliability, and significance and provide common solutions based on statistical methodology to solve them. The book focuses on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs). Based on the interpretable parameters of the trained GAMs or LMEMs, the book presents model-based statistical tests such as a validity test that allows for the detection of circular features that circumvent learning. Furthermore, the book discusses a reliability coefficient using variance decomposition based on random effect parameters of LMEMs. Lastly, a significance test based on the likelihood ratios of nested LMEMs trained on the performance scores of two machine learning models is shown to naturally allow the inclusion of variations in meta-parameter settings into hypothesis testing, and further facilitates a refined system comparison conditional on properties of input data. The book is self-contained with an appendix on the mathematical background of generalized additive models and linear mixed effects models as well as an accompanying webpage with the related R and Python code to replicate the presented experiments.The second edition also features a new hands-on chapter that illustrates how to use the included tools in practical applications.
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Sprache: Englisch
Verlag: Createspace Independent Publishing Platform, 2013
ISBN 10: 1490908951 ISBN 13: 9781490908953
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In den WarenkorbPaperback / softback. Zustand: New. Hagmann, Jean-Philippe (illustrator). This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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In den WarenkorbZustand: New. Print on Demand.
Sprache: Englisch
Verlag: Createspace Independent Publishing Platform, 2013
ISBN 10: 1490908951 ISBN 13: 9781490908953
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EUR 27,76
Anzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: new. Hagmann, Jean-Philippe (illustrator). Paperback. The world is becoming increasingly complex. Competition means that products are puffed up with additional functions and features. Services are extended and offered in many different variants. This complexity results in a high expediture of time, increased error proneness and leads to more customer queries and complaints. However, customers love simple products and services. Simple business processes make life easier. In "Simplicity for business success!" 5 principles and 14 strategies outline how to make products, services and processes simpler. Numerous examples assist in the implementation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 74,05
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In den WarenkorbZustand: New. Print on Demand.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND.
Sprache: Englisch
Verlag: Springer Nature Switzerland, Springer Nature Switzerland Jun 2024, 2024
ISBN 10: 3031570642 ISBN 13: 9783031570643
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science. The authors present problems of validity, reliability, and significance and provide common solutions based on statistical methodology to solve them. The book focuses on model-based empirical methods where data annotations and model predictions are treated as training data for interpretable probabilistic models from the well-understood families of generalized additive models (GAMs) and linear mixed effects models (LMEMs). Based on the interpretable parameters of the trained GAMs or LMEMs, the book presents model-based statistical tests such as a validity test that allows for the detection of circular features that circumvent learning. Furthermore, the book discusses a reliability coefficient using variance decomposition based on random effect parameters of LMEMs. Lastly, a significance test based on the likelihood ratios of nested LMEMs trained on the performance scores of two machine learning models is shown to naturally allow the inclusion of variations in meta-parameter settings into hypothesis testing, and further facilitates a refined system comparison conditional on properties of input data. The book is self-contained with an appendix on the mathematical background of generalized additive models and linear mixed effects models as well as an accompanying webpage with the related R and Python code to replicate the presented experiments. The second edition also features a new hands-on chapter that illustrates how to use the included tools in practical applications.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 188 pp. Englisch.