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152600369
Texts in Computer Science Computational Methods for Deep Learning: Theory, Algorithms, and Implementations, (Hardcover)
96% of respondents would recommend this to a friend
Item #:
152600369
FJD 206
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This book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence.
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What Stands Out
Comprehensive Coverage
This book provides a thorough exploration of deep learning methods including theory and practical algorithms, catering to both academic and industry professionals seeking to enhance their understanding of computational techniques.
Hands-On Implementations
Includes practical implementations alongside theoretical concepts, allowing readers to apply learned algorithms directly, which bridges the gap between theory and practice effectively for aspiring data scientists.
Expert Insights
Written by leading experts in the field, offering cutting-edge insights and methodologies that address current challenges in deep learning, making it a valuable resource for advancing one’s knowledge and skills.
Product Details
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Textbooks |
| Publication date | September, 2023 |
| Pages | 222 |
| Subgenre | Applied |
| Series title | Texts in Computer Science |
| Edition | 2nd second 2023 Edition |
| Publisher | Springer Nature Singapore |
| Original languages | English |
| Language | English |
| Edu focus | Mathematics |
| Educational level | College |
| Is collectible | N |
| Binding type | Case Binding |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.14 x 0.56 x 9.21 in (15.6 x 1.4 x 23.4 cm) |
| Assembled product weight | 1.14 lb (520 grams) |
| Bisac subject heading | Mathematics |
Who Should Buy?
-
Graduate Students
Ideal for graduate students studying deep learning, providing comprehensive theories and practical implementations to enhance their understanding.
-
Data Scientists
Great resource for data scientists interested in deep learning algorithms and computational methods to apply in real-world datasets.
-
Industry Professionals
Suitable for professionals seeking to update their knowledge or applications of deep learning techniques in their projects.
-
Beginners
Not suitable for beginners without prior knowledge as it dives deep into advanced concepts and complex algorithms.
Product Description
Texts in Computer Science Computational Methods for Deep Learning: Theory, Algorithms, and Implementations, (Hardcover)
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Wei Qi Yan All Books Editorial Review
Texts in Computer Science Computational Methods for Deep Learning: Theory, Algorithms, and Implementations is a comprehensive textbook published by Springer Nature Singapore in September 2023, focusing on applied mathematics for college-level education. This hardcover edition of 222 pages is ideal for those looking to deepen their understanding of deep learning through the exploration of theories and algorithms. The book is part of the reputable series 'Texts in Computer Science' and is primarily written in English, making it accessible to a broad audience interested in advanced computational methods.
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Pros
- High-quality hardcover format for durability
- Focuses on practical algorithms and implementations
- Well-structured for college education
- Part of a trusted academic series
- Published recently, ensuring up-to-date content
Cons
- The weight might be slightly heavy for some readers
Product Price History
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