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Understanding Deep Learning
85% of respondents would recommend this to a friend
HKD 577
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An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.
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產品詳情
| Publisher | The MIT Press |
| Publication date | December 5, 2023 |
| Language | English |
| File size | 42.8 MB |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 986 pages |
| ISBN-13 | 978-0262377102 |
| Page Flip | Enabled |
| Item Weight | 1.5 lbs (680 grams) |
Who Should Buy?
-
Aspiring Data Scientists
Perfect for individuals seeking foundational knowledge in deep learning and its practical applications in data science.
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AI Researchers
Offers advanced insights and methodologies valuable for researchers looking to deepen their understanding of deep learning techniques.
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Students in Technology
Ideal for students pursuing courses in AI, machine learning, or computer science, providing comprehensive learning materials.
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Complete Beginners
May not cater well to those without any background in programming or machine learning concepts.
產品敘述
Understanding Deep Learning
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AI & Semantics Editorial Review
Understanding Deep Learning is an essential resource published by The MIT Press, featuring a comprehensive 544 pages of deep learning concepts. The book balances theoretical foundations with practical applications, making it suitable for both beginners and experienced practitioners. Readers appreciate the clear exposition, well-structured chapters, and helpful diagrams that facilitate understanding of advanced topics like transformers and GANs. Many users highlight how the book's exercises effectively solidify learning, making it an invaluable tool for anyone serious about mastering deep learning.
Customer Reviews & Ratings
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優點
- Clear exposition of complex deep learning concepts
- Excellent balance between theory and practice
- Includes exercises for better comprehension
- Well-structured chapters with great diagrams
- Approachable for both beginners and experienced readers
缺點
- Some advanced topics may not be as strong
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HKD 577
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特色和優勢
- Provides authoritative treatment of deep learning
- Strikes a pragmatic middle ground between theory and practice
- Covers cutting-edge topics not found in existing texts
- Straddles theory and practice, giving the level of detail required to implement models
- Separates critical ideas from background context and extraneous detail
- Minimal mathematical prerequisites, extensive illustrations, and practice problems
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