Online-Ressource | |
Verfasst von: | Chaudhury, Krishnendu [VerfasserIn] |
Ashok, Ananya H. [VerfasserIn] | |
Narumanchi, Sujay [VerfasserIn] | |
Shankar, Devashish [VerfasserIn] | |
Titel: | Math and architectures of deep learning |
Mitwirkende: | Banerjee, Prithviraj [MitwirkendeR] |
Verf.angabe: | Krishnendu Chaudhury, with Ananya H. Ashok, Sujay Narumanchi, Devashish Shankar ; foreword by Prith Banerjee |
Verlagsort: | Shelter Island, NY |
Verlag: | Manning Publications |
E-Jahr: | 2024 |
Jahr: | [2024] |
Umfang: | 1 online resource (xxvi, 523 pages) |
Illustrationen: | illustrations. |
Fussnoten: | Includes index. - Description based on print version record |
ISBN: | 978-1-61729-648-2 |
1-61729-648-1 | |
Abstract: | Discover what's going on inside the black box! To work with deep learning you'll have to choose the right model, train it, preprocess your data, evaluate performance and accuracy, and deal with uncertainty and variability in the outputs of a deployed solution. This book takes you systematically through the core mathematical concepts, linear algebra, and Bayesian inference, all from a deep learning perspective. Math and archtectures of deep learning teaches the math, theory, and programming principles of deep learning models laid out side by side, and then puts them into practice with well-annotated Python code. You'll progrress from algebra, calculus, and statistics all the way to state-of-the-art DL architectures taken from the latest research. |
URL: | Aggregator: https://learning.oreilly.com/library/view/-/9781617296482/?ar |
Datenträger: | Online-Ressource |
Sprache: | eng |
Bibliogr. Hinweis: | Erscheint auch als : Druck-Ausgabe |
Sach-SW: | Apprentissage profond |
Apprentissage profond ; Mathématiques | |
Python (Langage de programmation) | |
Deep learning (Machine learning) | |
Python (Computer program language) | |
K10plus-PPN: | 1890483575 |
Lokale URL UB: | Zum Volltext |
Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg | |
Bestellen/Vormerken für Benutzer des Klinikums Mannheim Eigene Kennung erforderlich | |
Bibliothek/Idn: | UW / m4533709273 |
Lokale URL Inst.: | Zum Volltext |