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Seller: Bellwetherbooks, McKeesport, PA, U.S.A.
hardcover. Condition: Good. Bruise/tear to cover.
Seller: Bellwetherbooks, McKeesport, PA, U.S.A.
hardcover. Condition: Very Good. Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.
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hardcover. Condition: Fine. LIKE NEW!!! Has a red or black remainder mark on bottom/exterior edge of pages.
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Seller: Jadewalky Book Company, HANOVER PARK, IL, U.S.A.
Condition: Used - Very Good. A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.Probabilistic Machine Learning grew out of the author's 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Seller: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Seller: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condition: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Seller: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketHardcover. Condition: Brand New. 826 pages. 9.25x8.25x1.50 inches. In Stock.
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Language: English
Published by Mit Press, 2022
Seller: Books in my Basket, New Delhi, India
Hardcover. Condition: New. ISBN:9780262046824.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
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Add to basketHardcover. Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Seller: Russell Books, Victoria, BC, Canada
Hardcover. Condition: New. Special order direct from the distributor.
Seller: GoldBooks, Denver, CO, U.S.A.
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Language: English
Published by MIT Press Ltd Mär 2022, 2022
ISBN 10: 0262046822 ISBN 13: 9780262046824
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Neuware - A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author's 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based not Elektronisches Buch, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Condition: New. 2022. Hardcover. . . . . . Books ship from the US and Ireland.
Buch. Condition: Neu. Probabilistic Machine Learning | An Introduction | Kevin P. Murphy | Buch | Einband - fest (Hardcover) | Englisch | 2022 | MIT Press Ltd | EAN 9780262046824 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.