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linear algebra optimization machine learning von aggarwal charu (60 Ergebnisse)
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paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
paperback. Zustand: Very Good.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Bay State Book Company, North Smithfield, RI, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
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Hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Very Good.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Fine.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Good. Cover boards are slightly bowing/bending. Cover shows light scuffing/edge wear. Pages are clean, crisp, and unmarked. Text block has intact & firm binding. Good reading copy.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Fine.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Books From California, Simi Valley, CA, USA
Verkäuferbewertung 4 von 5 Sternen
hardcover. Zustand: Very Good. Cover and edges may have some wear.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Verlag: Springer
Anbieter: Academic Book Solutions, Medford, NY, USA
Verkäuferbewertung 5 von 5 Sternen
paperback. Zustand: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Verlag: Springer
Anbieter: Academic Book Solutions, Medford, NY, USA
Verkäuferbewertung 5 von 5 Sternen
paperback. Zustand: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
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Zustand: as new. Wie neu/Like new.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Jadewalky Book Company, HANOVER PARK, IL, USA
Verkäuferbewertung 1 von 5 Sternen
Zustand: Used - Very Good. This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows:1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts.2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The "parent problem" of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks.A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.
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Linear Algebra and Optimization for Machine Learning : A Textbook
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New.
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Linear Algebra and Optimization for Machine Learning : A Textbook
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: California Books, Miami, FL, USA
Verkäuferbewertung 4 von 5 Sternen
Zustand: New.
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Linear Algebra and Optimization for Machine Learning : A Textbook
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread book in perfect condition.
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Linear Algebra and Optimization for Machine Learning : A Textbook
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread book in perfect condition.
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Linear Algebra and Optimization for Machine Learning, 2nd Edition
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: 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 and Optimization for Machine Learning, 2nd Edition
Anbieter: Basi6 International, Irving, TX, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Linear Algebra and Optimization for Machine Learning (Hardcover)
Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031986180 ISBN 13: 9783031986185
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Verkäuferbewertung 5 von 5 Sternen
Hardcover. Zustand: new. Hardcover. This textbook is the second edition of the linear algebra and optimization book that was published in 2020. The exposition in this edition is greatly simplified as compared to the first edition. The second edition is enhanced with a large number of solved examples and exercises. A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning. It is common for machine learning practitioners to pick up missing bits and pieces of linear algebra and optimization via osmosis while studying the solutions to machine learning applications. However, this type of unsystematic approach is unsatisfying because the primary focus on machine learning gets in the way of learning linear algebra and optimization in a generalizable way across new situations and applications. Therefore, we have inverted the focus in this book, with linear algebra/optimization as the primary topics of interest, and solutions to machine learning problems as the applications of this machinery. In other words, the book goes out of its way to teach linear algebra and optimization with machine learning examples. By using this approach, the book focuses on those aspects of linear algebra and optimization that are more relevant to machine learning, and also teaches the reader how to apply them in the machine learning context. As a side benefit, the reader will pick up knowledge of several fundamental problems in machine learning. At the end of the process, the reader will become familiar with many of the basic linear-algebra- and optimization-centric algorithms in machine learning. Although the book is not intended to provide exhaustive coverage of machine learning, it serves as a technical starter for the key models and optimization methods in machine learning. Even for seasoned practitioners of machine learning, a systematic introduction to fundamental linear algebra and optimization methodologies can be useful in terms of providing a fresh perspective. The chapters of the book are organized as follows. 1-Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts. 2-Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The parent problem of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Linear Algebra and Optimization for Machine Learning : A Textbook
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 56,20
EUR 17,41 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New.
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Zustand: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Linear Algebra and Optimization for Machine Learning: A Textbook
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 60,72
EUR 13,90 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
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Zustand: New. pp. 495.
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Linear Algebra and Optimization for Machine Learning
Sprache: Englisch
Verlag: Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030403467 ISBN 13: 9783030403461
Paperback. Zustand: New. 2020 ed.
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Linear Algebra and Optimization for Machine Learning
Anbieter: PBShop.store US, Wood Dale, IL, USA
Verkäuferbewertung 5 von 5 Sternen
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Linear Algebra and Optimization for Machine Learning
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Verkäuferbewertung 4 von 5 Sternen
EUR 70,83
EUR 7,54 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
In den WarenkorbZustand: New. pp. 495.
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Linear Algebra and Optimization for Machine Learning
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
EUR 68,65
EUR 10,86 Versand
Versand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
