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Dark Queens and Their Quarry: Poems: Boneshadows of Motherskin: 2017-2019 & Hot Rod Butterfly: 2000-2014
Language: English
Published by Independently published, 2019
ISBN 10: 1692100335 ISBN 13: 9781692100339
Condition: New. King, Lisa (illustrator).
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![Seller image for American Art in the 20th Century : Painting and Sculpture, 1913 - 1993 [Paperback / English Edition] for sale by Specific Object / David Platzker](https://pictures.abebooks.com/inventory/md/md32125844327.jpg)
American Art in the 20th Century : Painting and Sculpture, 1913 - 1993 [Paperback / English Edition]
Language: English
Published by Royal Academy of Arts / Prestel-Verlag London / Munich, United Kingdom / Germany, 1993
ISBN 10: 3791312618 ISBN 13: 9783791312613
Seller: Specific Object / David Platzker, New York, NY, U.S.A.
Seller rating 5 out of 5 stars
503 pp.; 29.8 x 22 cm.; sewn bound; black-and-white & color; edition size unknown; unsigned and unnumbered; offset-printed Exhibition catalogue published in conjunction with show held at the Martin-Gropius-Bau, Berlin, May 8 - July 25, 1993. Traveled to the Royal Academy of Arts and the Saatchi Gallery, London, September 16 - December 12, 1993. Edited and with essays by Christos M. Joachimides, Norman Rosenthal, with co-ordinating editing by David Anfam. Additional essays by Brooks Adams, Richard Armstrong, John Beardsley, Neal Benezra, Achille Bonito Oliva, Arthur C. Danto, Abraham A. Davidson, Wolfgang Max Faust, Mary Emma Harris, Thomas Kellein, Donald Kuspit, Mary Lublin, Karal Ann Marling, Barbara Moore, Francis V. O'Connor, Stephen Polcari, Carter Ratcliff, Irving Sandler, Wieland Schmied, Peter Selz, Gail Stavitsky, and Douglas Tallack. Artists include Carl Andre, Richard Artschwager, Jean-Michel Basquiat, Jonathan Borofsky, James Lee Byars, Alexander Calder, John Chamberlain, Joseph Cornell, John Covert, Stuart Davis, Willem de Kooning, Charles Demuth, Arthur Dove, Marcel Duchamp, Dan Flavin, Sam Francis, Robert Gober, Arshile Gorky, Dan Graham, Philip Guston, David Hammons, Keith Haring, Marsden Hartley, Eva Hesse, Gary Hill, Jenny Holzer, Edward Hopper, Jasper Johns, Donald Judd, Mike Kelley, Ellsworth Kelly, Franz Kline, Jeff Koons, Sol LeWitt, Roy Lichtenstein, Robert Mangold, Brice Marden, Agnes Martin, Robert Morris, Gerald Murphy, Bruce Nauman, Barnett Newman, Georgia O'Keeffe, Claes Oldenburg, Jackson Pollock, Martin Puryear, Robert Rauschenberg, Man Ray, Ad Reinhardt, James Rosenquist, Mark Rothko, Edward Ruscha, Robert Ryman, Julian Schnabel, Richard Serra, Charles Sheeler, Cindy Sherman, David Smith, Frank Stella, Clyfford Still, James Turrell, Cy Twombly, Bill Viola, Andy Warhol, and Lawrence Weiner. Includes exhibition checklist, a list of artists in the exhibition, biographies of the artists, selected bibliography, author biographies, and an index of names. Text in English. Good. 5.5 cm. dog-ear to bottom right corner of recto and 9.5 cm. crease to top right corner of recto with bumping of corners. Light yellowing of pages. Contents clean and unmarked. Due to large size and weight additional shipping charges will be required for international orders.
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Linear Algebra, Data Science, and Machine Learning (Springer Undergraduate Texts in Mathematics and Technology)
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Good.
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Linear Algebra, Data Science, and Machine Learning (Springer Undergraduate Texts in Mathematics and Technology)
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Very Good.
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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.
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Linear Algebra, Data Science, and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Condition: As New. Unread book in perfect condition.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Linear Algebra, Data Science and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Linear Algebra, Data Science, and Machine Learning (Hardcover)
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologyLanguage: English
Published by Springer International Publishing AG, Cham, 2025
ISBN 10: 3031937635 ISBN 13: 9783031937637
Hardcover. Condition: new. Hardcover. This text provides a mathematically rigorous introduction to modern methods of machine learning and data analysis at the advanced undergraduate/beginning graduate level. The book is self-contained and requires minimal mathematical prerequisites. There is a strong focus on learning how and why algorithms work, as well as developing facility with their practical applications. Apart from basic calculus, the underlying mathematics linear algebra, optimization, elementary probability, graph theory, and statistics is developed from scratch in a form best suited to the overall goals. In particular, the wide-ranging linear algebra components are unique in their ordering and choice of topics, emphasizing those parts of the theory and techniques that are used in contemporary machine learning and data analysis. The book will provide a firm foundation to the reader whose goal is to work on applications of machine learning and/or research into the further development of this highly active field of contemporary applied mathematics.To introduce the reader to a broad range of machine learning algorithms and how they are used in real world applications, the programming language Python is employed and offers a platform for many of the computational exercises. Python notebooks complementing various topics in the book are available on a companion GitHub site specified in the Preface, and can be easily accessed by scanning the QR codes or clicking on the links provided within the text. Exercises appear at the end of each section, including basic ones designed to test comprehension and computational skills, while others range over proofs not supplied in the text, practical computations, additional theoretical results, and further developments in the subject. The Students Solutions Manual may be accessed from GitHub. Instructors may apply for access to the Instructors Solutions Manual from the link supplied on the texts Springer website.The book can be used in a junior or senior level course for students majoring in mathematics with a focus on applications as well as students from other disciplines who desire to learn the tools of modern applied linear algebra and optimization. It may also be used as an introduction to fundamental techniques in data science and machine learning for advanced undergraduate and graduate students or researchers from other areas, including statistics, computer science, engineering, biology, economics and finance, and so on. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Linear Algebra Data Science & Machine Le
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Linear Algebra, Data Science and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologySeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Hardcover. Condition: Brand New. 652 pages. 10.00x7.00x10.00 inches. In Stock.
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Dark Queens and Their Quarry: Poems: Boneshadows of Motherskin: 2017-2019 & Hot Rod Butterfly: 2000-2014
Language: English
Published by Independently published, 2019
ISBN 10: 1692100335 ISBN 13: 9781692100339
Condition: New. King, Lisa (illustrator). Print on Demand.
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Linear Algebra, Data Science, and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologyLanguage: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031937635 ISBN 13: 9783031937637
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New.
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Linear Algebra, Data Science, and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologyLanguage: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031937635 ISBN 13: 9783031937637
Hardback. Condition: New.
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BMW Art Cars
Seller: Nightshade Booksellers, IOBA member, Atlanta, GA, U.S.A.
Association Member: IOBA
Seller rating 5 out of 5 stars
First Edition
Hardcover. Condition: Fine. Andy Warhol, Alexander Calder, David Hockney, Jeff Koons, Roy Lichtenstein, et al (illustrator). 1st Edition. First edition. A fine copy in a fine slipcase. A fabulous book with BMWs interpreted by many iconic artists. See my photos of the book you will receive, not stock photos. More available upon request. This book is in my possession and will be packed in bubble wrap and shipped in a cardboard box. USPS tracking provided. #140.
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International EditionHardcover. 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 7-12 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.
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Hardcover. Condition: Brand New. 652 pages. 10.00x7.00x10.00 inches. In Stock.
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Linear Algebra, Data Science, and Machine Learning
Book 32 of 32: Springer Undergraduate Texts in Mathematics and TechnologyLanguage: English
Published by Springer International Publishing AG Sep 2025, 2025
ISBN 10: 3031937635 ISBN 13: 9783031937637
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This text provides a mathematically rigorous introduction to modern methods of machine learning and data analysis at the advanced undergraduate/beginning graduate level. The book is self-contained and requires minimal mathematical prerequisites. There is a strong focus on learning how and why algorithms work, as well as developing facility with their practical applications. Apart from basic calculus, the underlying mathematics linear algebra, optimization, elementary probability, graph theory, and statistics is developed from scratch in a form best suited to the overall goals. In particular, the wide-ranging linear algebra components are unique in their ordering and choice of topics, emphasizing those parts of the theory and techniques that are used in contemporary machine learning and data analysis. The book will provide a firm foundation to the reader whose goal is to work on applications of machine learning and/or research into the further development of this highly active field of contemporary applied mathematics.To introduce the reader to a broad range of machine learning algorithms and how they are used in real world applications, the programming language Python is employed and offers a platform for many of the computational exercises. Python not Elektronisches Buch complementing various topics in the book are available on a companion GitHub site specified in the Preface, and can be easily accessed by scanning the QR codes or clicking on the links provided within the text. Exercises appear at the end of each section, including basic ones designed to test comprehension and computational skills, while others range over proofs not supplied in the text, practical computations, additional theoretical results, and further developments in the subject. The Students Solutions Manual may be accessed from GitHub. Instructors may apply for access to the Instructors Solutions Manual from the link supplied on the text s Springer website.The book can be used in a junior or senior level course for students majoring in mathematics with a focus on applications as well as students from other disciplines who desire to learn the tools of modern applied linear algebra and optimization. It may also be used as an introduction to fundamental techniques in data science and machine learning for advanced undergraduate and graduate students or researchers from other areas, including statistics, computer science, engineering, biology, economics and finance, and so on.
