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Linear Algebra and Learning from Data, Strang Gilbert


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Цена: 9978.00р.
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Автор: Strang Gilbert   (Гилберт Странг)
Название:  Linear Algebra and Learning from Data
Перевод названия: Гилберт Странг: Линейная алгебра и обучение на основе данных
ISBN: 9780692196380
Издательство: Cambridge Academ
Классификация:
ISBN-10: 0692196382
Обложка/Формат: Hardback
Страницы: 446
Вес: 0.93 кг.
Дата издания: 31.01.2019
Серия: Mathematics
Язык: English
Иллюстрации: Worked examples or exercises
Размер: 239 x 204 x 19
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Maths for computer scientists,Machine learning,Pattern recognition,Mathematical modelling, COMPUTERS / Computer Vision & Pattern Recognition
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.


Linear Algebra

Автор: Singh Kuldeep
Название: Linear Algebra
ISBN: 0199654441 ISBN-13(EAN): 9780199654444
Издательство: Oxford Academ
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Цена: 5146.00 р.
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Описание: Linear algebra is a fundamental area of mathematics, and arguably the most powerful mathematical tool ever developed. This dynamic and engaging book uses numerous examples, question and answer sections, and historical biographies to provide an introduction to linear algebra for undergraduates in mathematics, the physical sciences and engineering.

Computational Methods Of Linear Algebra (3Rd Edition)

Автор: Sewell Granville
Название: Computational Methods Of Linear Algebra (3Rd Edition)
ISBN: 9814603864 ISBN-13(EAN): 9789814603867
Издательство: World Scientific Publishing
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Цена: 6336.00 р.
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Описание: This book presents methods for the computational solution of some important problems of linear algebra: linear systems, linear least squares problems, eigenvalue problems, and linear programming problems.

Computational Methods Of Linear Algebra (3Rd Edition)

Автор: Sewell Granville
Название: Computational Methods Of Linear Algebra (3Rd Edition)
ISBN: 9814603856 ISBN-13(EAN): 9789814603850
Издательство: World Scientific Publishing
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Цена: 11563.00 р.
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Описание: This book presents methods for the computational solution of some important problems of linear algebra: linear systems, linear least squares problems, eigenvalue problems, and linear programming problems.

Elementary Linear Algebra

Автор: Kirkwood
Название: Elementary Linear Algebra
ISBN: 149877685X ISBN-13(EAN): 9781498776851
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: This is the second of a two-part set of books for the undergraduate linear algebra sequence. The text is for more advanced courses taught in mathematics departments. This course is based around matrix theory and focused on the theory of linear algebra. Along with the chapters found in Elementary Linear Algebra, he offers seven additional chapters .

The theory of quantum information

Автор: Watrous, John (university Of Waterloo, Ontario)
Название: The theory of quantum information
ISBN: 1107180562 ISBN-13(EAN): 9781107180567
Издательство: Cambridge Academ
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Цена: 11563.00 р.
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Описание: Intended for graduate students and researchers, this book presents a formal development of the mathematical theory of quantum information. Largely self-contained, with clear proofs and a wide range of exercises, it will help the reader grasp the fundamental facts and techniques that form the mathematical foundations of the subject.

Computational Linear and Commutative Algebra

Автор: Kreuzer
Название: Computational Linear and Commutative Algebra
ISBN: 331943599X ISBN-13(EAN): 9783319435992
Издательство: Springer
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Цена: 7406.00 р.
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Описание: This book combines, in a novel and general way, an extensive development of the theory of families of commuting matrices with applications to zero-dimensional commutative rings, primary decompositions and polynomial system solving. It integrates the Linear Algebra of the Third Millennium, developed exclusively here, with classical algorithmic and algebraic techniques. Even the experienced reader will be pleasantly surprised to discover new and unexpected aspects in a variety of subjects including eigenvalues and eigenspaces of linear maps, joint eigenspaces of commuting families of endomorphisms, multiplication maps of zero-dimensional affine algebras, computation of primary decompositions and maximal ideals, and solution of polynomial systems. This book completes a trilogy initiated by the uncharacteristically witty books Computational Commutative Algebra 1 and 2 by the same authors. The material treated here is not available in book form, and much of it is not available at all. The authors continue to present it in their lively and humorous style, interspersing core content with funny quotations and tongue-in-cheek explanations.

Introduction to Applied Linear Algebra

Автор: Boyd Stephen
Название: Introduction to Applied Linear Algebra
ISBN: 1316518965 ISBN-13(EAN): 9781316518960
Издательство: Cambridge Academ
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Цена: 6811.00 р.
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Описание: A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
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Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book

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