Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 34,64
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Añadir al carritopaperback. Condición: Very Good. Cover and edges may have some wear.
Idioma: Inglés
Publicado por Springer International Publishing AG, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Librería: Better World Books, Mishawaka, IN, Estados Unidos de America
EUR 52,11
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Añadir al carritoCondición: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 61,02
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 62,23
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Librería: Hawking Books, Edgewood, TX, Estados Unidos de America
EUR 67,27
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Añadir al carritoCondición: Very Good. Very Good Condition. Five star seller - Buy with confidence!
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 72,44
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Librería: Chiron Media, Wallingford, Reino Unido
EUR 69,20
Cantidad disponible: 10 disponibles
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 72,14
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 80,75
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 92,92
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Añadir al carritoCondición: New. pp. 384.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 78,74
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 94,56
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Añadir al carritoPaperback. Condición: Brand New. 2nd edition. 400 pages. 9.25x6.10x0.94 inches. In Stock.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 101,25
Cantidad disponible: 15 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 64,19
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples.This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated \*Programming Tips\* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras.This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.
EUR 59,30
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Python for Probability, Statistics, and Machine Learning | José Unpingco | Taschenbuch | xiv | Englisch | 2020 | Springer | EAN 9783030185473 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 112,75
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Añadir al carritoPaperback. Condición: New. New. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 54,23
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Aug 2020, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 64,19
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples.This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated \*Programming Tips\* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras.This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming. 400 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 92,63
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand pp. 384.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 91,48
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND pp. 384.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Librería: moluna, Greven, Alemania
EUR 55,78
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Features fully updated explanation on how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methodsNew edition features Python version 3.7 and connects to key open-source Python communities and corre.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Aug 2020, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 64,19
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 400 pp. Englisch.