Pattern Recognition and Machine Learning
(9780387310732) - Dimensions: 178 x 254 x 43.18mm | 2,147g - Edition: 1st ed. 2006. Corr. 2nd printing 2011 - Format: 738 pages - ISBN: 9780387310732 - Number of pages: 738 - Languages: English - Publication place: New York, NY, United States
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This is the first textbook on pattern recognition to present the Bayesian viewpoint. It provides an accessible introduction to approximate inference algorithms that allow for fast, approximate answers in situations where exact answers are not feasible. With its use of graphical models to describe probability distributions, this book is a great resource for those with no prior knowledge of pattern recognition or machine learning concepts. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful, though not essential as the book includes a self-contained introduction to basic probability theory.
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| Tags | Pattern Pattern Recognition Pattern Machine Pattern Learning Pattern Information Pattern Science Pattern Statistics Pattern Recognition Machine Pattern Recognition Learning Pattern Machine Learning Pattern Information Science Pattern Information Statistics Pattern Science Statistics Pattern Recognition Information Pattern Recognition Statistics |
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| Brand |  Springer is a German brand that produces high-quality bicycles. The company has a rich history, dating back to 1885, and is known for its innovative designs and quality products. Springer bikes are popular among cyclists of all levels, and the brand is known for its commitment to customer satisfaction. |
| ISBN | Springer 0387310738 |
| ID | 2533867 |
| Dimensions / Weight | |
| Key Features | |
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Dimensions The pixel dimensions of a display or image, expressed as width by height (e.g., 1920x1080). It indicates how many pixels are used to render the visual content and is commonly used for monitors, TVs, smartphones, cameras, and digital images.
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178 x 254 x 43.18mm | 2,147g |
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Edition A brief statement indicating the edition or version of a product, such as "Reprint", "New Edition", or a numeric edition number like "2nd edition". It identifies which specific release of the item is being referenced.
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1st ed. 2006. Corr. 2nd printing 2011 |
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Format Indicates the physical or digital format in which a product is presented, such as "Hardback", "Paperback", "DVD", "Blu‑ray", "Vinyl", or other media types. The value may contain multiple comma‑separated items to represent combined attributes (e.g., "Hardback, Illustrated").
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738 pages |
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ISBN A unique identifier assigned to books and other printed publications, typically consisting of 10 or 13 digits. It may include hyphens for readability but is treated as a string value. The ISBN uniquely identifies a specific edition of a title across the publishing industry.
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9780387310732 |
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Languages A list of the natural languages in which a product is available or supported.
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English |
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Publication place The city, town, or region where a product was first published, released, or made available to the public. It typically includes geographic identifiers such as city names, state or province abbreviations, and country names, and may also contain postal codes or other location details.
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New York, NY, United States |
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Publisher The name of the entity that publishes or distributes the product, such as a book, magazine, or other media item.
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Springer-Verlag New York Inc. |
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Weight The mass of the product expressed in a standard unit such as grams or kilograms. It represents how heavy the item is and can be used for shipping calculations, handling instructions, or consumer information.
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2147 g |
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(9781138626782) - Edition: 1st edition - Publication date: 26 Sep 2017 - Height: 163mm - Spine width: 30mm - Width: 240mm - Chapman & Hall/CRC - Taylor and Francis - ISBN: 9781138626782 - Number of pages: 364
A comprehensive guide that blends statistical theory with practical algorithms, covering Bayesian inference, neural networks, and support vector machines to master pattern recognition and machine learning.
(9781138626782) - Edition: 1st edition - Publication date: 26 Sep 2017 - Height: 163mm - Spine width: 30mm - Width: 240mm - Chapman & Hall/CRC - Taylor and Francis - ISBN: 9781138626782 - Number of pages: 364
A comprehensive guide that blends statistical theory with practical algorithms, covering Bayesian inference, neural networks, and support vector machines to master pattern recognition and machine learning.
