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Item #:
87943750
Technology that supports deep learning —— Mechanisms that lead to correct answers Technology basics Tech × Books plus Tankobon Softcover –
89% of respondents would recommend this to a friend
Item #:
87943750
SAR 108
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Product Details
| Publisher | u6280u8853u8a55u8ad6u793e (January 8, 2022) |
| Publication date | January 8, 2022 |
| Language | Japanese |
| Tankobon Softcover | 304 pages |
| ISBN-10 | 4297125609 |
| ISBN-13 | 978-4297125608 |
| Dimensions | 5.83 x 0.63 x 8.27 inches (14.8 x 1.6 x 21 cm) |
Who Should Buy?
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Deep Learning Enthusiasts
Individuals interested in understanding deep learning mechanisms and their application in obtaining correct answers.
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Students and Educators
Useful for students learning about deep learning concepts and educators who are teaching the subject.
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Data Scientists
Professionals in the data science field seeking to enhance their knowledge of deep learning technologies.
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Casual Readers
Individuals looking for light reading material unrelated to deep learning or technology concepts.
Product Description
Technology that supports deep learning —— Mechanisms that lead to correct answers Technology basics Tech × Books plus Tankobon Softcover – January 8, 2022
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岡野原 大輔 Editorial Review
### Editorial Review The product under review is a well-regarded introduction to deep learning techniques, specifically aimed at readers with an interest in the subject but who may not possess extensive background knowledge. Customers appreciate the author’s ability to distill complex concepts into clear, comprehensible explanations, enriched with metaphors and organized presentation that facilitate understanding. Reviewers commend the strong focus on essential points, making it particularly suitable for those new to the field. One of the standout features is the inclusion of illustrations that effectively clarify challenging topics, enhancing the overall readability of the text. The author is recognized for their expertise, providing a nuanced overview of contemporary AI applications and mathematical foundations without overwhelming the reader with excessive equations. However, some reviewers suggest that the highlighted text could be distracting, indicating a preference for a cleaner presentation format. Despite its accessibility, several customers caution that the book is not strictly for absolute beginners and might be more beneficial for those with some preliminary knowledge. While it serves as a solid primer, readers looking for practical coding examples may find it lacking, as the focus is on theoretical understanding rather than hands-on implementation. This makes the book ideal for readers aiming to gain a broader perspective on deep learning before delving deeper into specific programming tasks or applications. Overall, the reception of the product is positive, with clear advantages in terms of its structured approach to deep learning fundamentals, though it may not cater to all learning styles or needs. ### Pros and Cons **
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Pros
- Clear and comprehensible explanations of complex concepts
- Effective use of metaphors and organized presentation
- Strong focus on essential points, suitable for newcomers
- Illustrations that clarify difficult topics
- Author's expertise provides valuable insights into contemporary AI applications
Cons
- The highlighted text may be distracting for some readers
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