Paperback. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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In den WarenkorbZustand: New.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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In den WarenkorbPaperback. Zustand: Brand New. 450 pages. 9.25x7.37x1.12 inches. In Stock.
Sprache: Englisch
Verlag: Manning Publications, United States, New York, 2024
ISBN 10: 1617296481 ISBN 13: 9781617296482
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
EUR 80,48
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In den WarenkorbPaperback. Zustand: Very Good. The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learningbridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you'll peer inside the black box to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. about the technology It's important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You'll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you'll be glad you can quickly identify and fix problems. about the book Math and Architectures of Deep Learningsets out the foundations of DL in a way that's both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You'll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you're done, you'll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
EUR 93,27
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In den WarenkorbPaperback. Zustand: Brand New. 450 pages. 9.25x7.37x1.12 inches. In Stock.
Kartoniert / Broschiert. Zustand: New. Über den AutorKrishnendu Chaudhury is a deep learning and computer vision expert with decade-long stints at both Google and Adobe Systems. He is presently CTO and co-founder of Drishti Technologies. He has a PhD in computer s.
Sprache: Englisch
Verlag: Manning Publications Mär 2024, 2024
ISBN 10: 1617296481 ISBN 13: 9781617296482
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Shine a spotlight into the deep learning "black box". This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively.Inside Math and Architectures of Deep Learning you will find:
Taschenbuch. Zustand: Neu. Math and Architectures of Deep Learning | Krishnendu Chaudhury | Taschenbuch | Kartoniert / Broschiert | Englisch | 2024 | Manning Publications | EAN 9781617296482 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.