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Mathematical aspects of deep learning

By: Grohs, Philipp [ed.].
Contributor(s): Kutyniok, Gitta [ed.].
Publisher: Cambridge : Cambridge University Press 2023Description: xviii, 473 p. ; ill., 25 cm.ISBN: 9781316516782.Subject(s): Activation function | Deep neural networks | Neural networks | Universal approximation | WaveletDDC classification: 006.310151 Summary: In Modern Software Engineering, continuous delivery pioneer David Farley helps software professionals think about their work more effectively, manage it more successfully, and genuinely improve the quality of their applications, their lives, and the lives of their colleagues. Writing for programmers, managers, and technical leads at all levels of experience, Farley illuminates durable principles at the heart of effective software development. He distills the discipline into two core exercises: learning and exploration and managing complexity. For each, he defines principles that can help you improve everything from your mindset to the quality of your code, and describes approaches proven to promote success.
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Books 006.310151 GRO (Browse shelf) Available 034285

Includes bibliographical references.

In Modern Software Engineering, continuous delivery pioneer David Farley helps software professionals think about their work more effectively, manage it more successfully, and genuinely improve the quality of their applications, their lives, and the lives of their colleagues. Writing for programmers, managers, and technical leads at all levels of experience, Farley illuminates durable principles at the heart of effective software development. He distills the discipline into two core exercises: learning and exploration and managing complexity. For each, he defines principles that can help you improve everything from your mindset to the quality of your code, and describes approaches proven to promote success.

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