Paperback. Very Good. ISBN 0262018020 9780262018029 [GB]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press] Hardcover 100% Customer Satisfaction Guaranteed ! The book shows some signs of wear from use but is a good readable copy. Cover in excellent condition. Binding tight. Pages in great shape, no tears. Not contain access codes, cd, DVD.
[Suffolk, United Kingdom] [Publication Year: 2012]
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The MIT Press, 8/24/Date: 2012. Illustrated. hardcover. Acceptable. 8x1x9. DAMAGED - Acceptable Condition and Unread! Text is clean and unmarked! Bruise/tear/crease to cover. Has a small black line or red dot on bottom/exterior edge of pages. 2012. The MIT Press ISBN 0262018020 9780262018029 [US]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover SHIPS FROM USA. Used books have different signs of use and do not include supplemental materials such as CDs, Dvds, Access Codes, charts or any other extra material. All used books might have various degrees of writing, highliting and wear and tear and possibly be an ex-library with the usual stickers and stamps. Dust Jackets are not guaranteed and when still present, they will have various degrees of tear and damage. All images are Stock Photos, not of the actual item.
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press (edition Illustrated)] Hardcover Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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The MIT Press. Illustrated. Very Good. Very Good. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported The MIT Press ISBN 0262018020 9780262018029 [US]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover This item is in overall acceptable condition. Covers and dust jackets are intact but may have heavy wear including creases, bends, edge wear, curled corners or minor tears as well as stickers or sticker-residue. Pages are intact but may have minor curls, bends or moderate to considerable highlighting/ writing. Binding is intact; however, spine may have heavy wear. Digital codes may not be included and have not been tested to be redeemable and/or active. A well-read copy overall. Please note that all items are donated goods and are in used condition. Orders shipped Monday through Friday! Your purchase helps put people to work and learn life skills to reach their full potential. Orders shipped Monday through Friday. Your purchase helps put people to work and learn life skills to reach their full potential. Thank you!
[COLORADO SPRINGS, CO, U.S.A.] [Publication Year: 2012]

Cambridge, MA: MIT, Date: 2012. Fifth Printing. Hardcover. Near fine. Thick octavo. 8 x 9.5 in.1070 pp. Near fine in original pictorial paper-covered boards, no dust jacket and a previous owner signature to front paste-down endpaper. 2012. MIT ISBN 0262018020 9780262018029 [US]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Ausreichend/Acceptable: Exemplar mit vollständigem Text und sämtlichen Abbildungen oder Karten. Schmutztitel oder Vorsatz können fehlen. Einband bzw. Schutzumschlag weisen unter Umständen starke Gebrauchsspuren auf. / Describes a book or dust jacket that has the complete text pages (including those with maps or plates) but may lack endpapers, half-title, etc. (which must be noted). Binding, dust jacket (if any), etc may also be worn.
[Berlin, Germany] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Book is in Used-Good condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain limited notes and highlighting.
[Hawthorne, CA, U.S.A.] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover New. Fast Shipping and good customer service
[Fayetteville, TX, U.S.A.] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Ausreichend/Acceptable: Exemplar mit vollständigem Text und sämtlichen Abbildungen oder Karten. Schmutztitel oder Vorsatz können fehlen. Einband bzw. Schutzumschlag weisen unter Umständen starke Gebrauchsspuren auf. / Describes a book or dust jacket that has the complete text pages (including those with maps or plates) but may lack endpapers, half-title, etc. (which must be noted). Binding, dust jacket (if any), etc may also be worn.
[Berlin, Germany] [Publication Year: 2012]

Mit Press 2012 Hard cover New Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Cambridge Mit Press 2012 Hard cover Good. Sewn binding. Cloth over boards. 1104 p. Contains: Illustrations, black & white, Illustrations, color. Adaptive Computation and Machine Learning. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Used Book
[STAFFORD, TX, U.S.A.] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Very Good Copy. Customer Service Guaranteed
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press] Hardcover Book is in NEW condition. Satisfaction Guaranteed! Fast Customer Service!!
[Suffolk, United Kingdom] [Publication Year: 2012]
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press Ltd Aug 2012] Hardcover Neuware - A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package PMTK (probabil ...
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Prompt service guaranteed.
[Tijeras, NM, U.S.A.] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press] Hardcover New Book. Shipped from UK. Established seller since 2000.
[Fairford, GLOS, United Kingdom] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: The MIT Press] Hardcover Book is in NEW condition.
[Hawthorne, CA, U.S.A.] [Publication Year: 2012]

ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press Ltd Aug 2012] Hardcover Neuware - A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package PMTK (probabil ...
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ISBN10: 0262018020, ISBN13: 9780262018029, [publisher: MIT Press Ltd, Cambridge, Mass.] Hardcover Hardcover. A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package-PMTK ...
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