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The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec.
Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines.
Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10.
The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec.
Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines.
Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10.
The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
Erscheinungsjahr: | 2019 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xxiii
497 S. 128 s/w Illustr. 11 farbige Illustr. 497 p. 139 illus. 11 illus. in color. |
ISBN-13: | 9783030068561 |
ISBN-10: | 3030068560 |
Sprache: | Englisch |
Herstellernummer: | 978-3-030-06856-1 |
Ausstattung / Beilage: | Previously published in hardcover |
Autor: | Aggarwal, Charu C. |
Auflage: | Softcover reprint of the original 1st ed. 2018 |
Hersteller: |
Springer
Springer, Berlin Springer International Publishing |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Abbildungen: | XXIII, 497 p. 139 illus., 11 illus. in color. |
Maße: | 29 x 180 x 254 mm |
Von/Mit: | Charu C. Aggarwal |
Erscheinungsdatum: | 31.01.2019 |
Gewicht: | 0,986 kg |
Erscheinungsjahr: | 2019 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xxiii
497 S. 128 s/w Illustr. 11 farbige Illustr. 497 p. 139 illus. 11 illus. in color. |
ISBN-13: | 9783030068561 |
ISBN-10: | 3030068560 |
Sprache: | Englisch |
Herstellernummer: | 978-3-030-06856-1 |
Ausstattung / Beilage: | Previously published in hardcover |
Autor: | Aggarwal, Charu C. |
Auflage: | Softcover reprint of the original 1st ed. 2018 |
Hersteller: |
Springer
Springer, Berlin Springer International Publishing |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Abbildungen: | XXIII, 497 p. 139 illus., 11 illus. in color. |
Maße: | 29 x 180 x 254 mm |
Von/Mit: | Charu C. Aggarwal |
Erscheinungsdatum: | 31.01.2019 |
Gewicht: | 0,986 kg |