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Calculus / Gilbert Strang

Public ISBD Titre : Calculus Type de document : texte imprimé Auteurs : Gilbert Strang, Auteur Editeur : Wellesley-Cambridge Press, Wellesley, MA. Importance : 615 pages [A] Présentation : illustrations Langues : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:515 Analyse Index. décimale : 515 Calculus [texte imprimé] / Gilbert Strang, Auteur . - [S.l.] : Wellesley-Cambridge Press, Wellesley, MA., [s.d.] . - 615 pages [A] : illustrations. Langues : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:515 Analyse Index. décimale : 515

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Linear algebra and learning from data / Gilbert Strang

Public ISBD Titre : Linear algebra and learning from data Type de document : texte imprimé Auteurs : Gilbert Strang, Auteur; Kiminori Matsuzaki, Traducteur Editeur : Wellesley-Cambridge Press, Wellesley, MA. Année de publication : 2019 Importance : xiii 432 Pages Présentation : illustrations black and white Format : 19.50cmx24cm ISBN/ISSN/EAN : 978-0-692-19638-0 Langues : Anglais (eng) Langues originales : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:512 Algèbre et théorie des nombres:512.5 Algèbres linéaire, multilinéaire, multidimensionnelle Mots-clés : Linear algebra and learning from data Index. décimale : 512.5 Résumé : This is a textbook to help readers understand the steps that lead to deep learning. Linear algebra comes first especially singular values, least squares, and matrix factorizations. Often the goal is a low rank approximation A = CR (column-row) to a large matrix of data to see its most important part. This uses the full array of applied linear algebra, including randomization for very large matrices. Then deep learning creates a large-scale optimization problem for the weights solved by gradient descent or better stochastic gradient descent. Finally, the book develops the architectures of fully connected neural nets and of Convolutional Neural Nets (CNNs) to find patterns in data. Audience: This book is for anyone who wants to learn how data is reduced and interpreted by and understand matrix methods. Based on the second linear algebra course taught by Professor Strang, whose lectures on the training data are widely known, it starts from scratch (the four fundamental subspaces) and is fully accessible without the first text. -- Publisher’s description Linear algebra and learning from data [texte imprimé] / Gilbert Strang, Auteur; Kiminori Matsuzaki, Traducteur . - [S.l.] : Wellesley-Cambridge Press, Wellesley, MA., 2019 . - xiii 432 Pages : illustrations black and white ; 19.50cmx24cm. ISBN : 978-0-692-19638-0 Langues : Anglais (eng) Langues originales : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:512 Algèbre et théorie des nombres:512.5 Algèbres linéaire, multilinéaire, multidimensionnelle Mots-clés : Linear algebra and learning from data Index. décimale : 512.5 Résumé : This is a textbook to help readers understand the steps that lead to deep learning. Linear algebra comes first especially singular values, least squares, and matrix factorizations. Often the goal is a low rank approximation A = CR (column-row) to a large matrix of data to see its most important part. This uses the full array of applied linear algebra, including randomization for very large matrices. Then deep learning creates a large-scale optimization problem for the weights solved by gradient descent or better stochastic gradient descent. Finally, the book develops the architectures of fully connected neural nets and of Convolutional Neural Nets (CNNs) to find patterns in data. Audience: This book is for anyone who wants to learn how data is reduced and interpreted by and understand matrix methods. Based on the second linear algebra course taught by Professor Strang, whose lectures on the training data are widely known, it starts from scratch (the four fundamental subspaces) and is fully accessible without the first text. -- Publisher’s description

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Introduction to linear algebra / Gilbert Strang

Public ISBD Titre : Introduction to linear algebra Type de document : texte imprimé Auteurs : Gilbert Strang, Auteur Mention d'édition : sixth edition Editeur : Wellesley-Cambridge Press, Wellesley, MA. Année de publication : 2023 Importance : x, 430 pages Présentation : illustrations Format : 24 cm ISBN/ISSN/EAN : 978-1-7331-4667-8 Langues : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:512 Algèbre et théorie des nombres:512.5 Algèbres linéaire, multilinéaire, multidimensionnelle Mots-clés : Introduction to linear algebra Index. décimale : 512.5 Résumé : Linear algebra now rivals or surpasses calculus in importance for people working in quantitative fields of all kinds: engineers, scientists, economists and business people. Gilbert Strang has taught linear algebra at MIT for more than 50 years and the course he developed has become a model for teaching around the world. His video lectures on MIT OpenCourseWare have been viewed over ten million times and his twelve textbooks are popular with readers worldwide. This sixth edition of Professor Strang's most popular book, Introduction to Linear Algebra, introduces the ideas of independent columns and the rank and column space of a matrix early on for a more active start. Then the book moves directly to the classical topics of linear equations, fundamental subspaces, least squares, eigenvalues and singular values - in each case expressing the key idea as a matrix factorization. The final chapters of this edition treat optimization and learning from data: the most active application of linear algebra today. Everything is explained thoroughly in Professor Strang's characteristic clear style. It is sure to delight and inspire the delight and inspire the next generation of learners. -- Provided by publisher Introduction to linear algebra [texte imprimé] / Gilbert Strang, Auteur  . -  sixth edition . - [S.l.] : Wellesley-Cambridge Press, Wellesley, MA., 2023 . - x, 430 pages : illustrations ; 24 cm. ISBN : 978-1-7331-4667-8 Langues : Anglais (eng) Catégories : 540 Chimie et sciences connexes:500 Sciences de la nature et mathématiques:512 Algèbre et théorie des nombres:512.5 Algèbres linéaire, multilinéaire, multidimensionnelle Mots-clés : Introduction to linear algebra Index. décimale : 512.5 Résumé : Linear algebra now rivals or surpasses calculus in importance for people working in quantitative fields of all kinds: engineers, scientists, economists and business people. Gilbert Strang has taught linear algebra at MIT for more than 50 years and the course he developed has become a model for teaching around the world. His video lectures on MIT OpenCourseWare have been viewed over ten million times and his twelve textbooks are popular with readers worldwide. This sixth edition of Professor Strang's most popular book, Introduction to Linear Algebra, introduces the ideas of independent columns and the rank and column space of a matrix early on for a more active start. Then the book moves directly to the classical topics of linear equations, fundamental subspaces, least squares, eigenvalues and singular values - in each case expressing the key idea as a matrix factorization. The final chapters of this edition treat optimization and learning from data: the most active application of linear algebra today. Everything is explained thoroughly in Professor Strang's characteristic clear style. It is sure to delight and inspire the delight and inspire the next generation of learners. -- Provided by publisher

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