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Item #:
18006456
Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
89% of respondents would recommend this to a friend
Item #:
18006456
XAF 44433
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Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.
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What Stands Out
Comprehensive Coverage
This book offers an in-depth exploration of deep learning concepts, equipping readers with a thorough understanding of adaptive computation techniques necessary for advanced applications in artificial intelligence.
Practical Applications
Includes real-world examples and case studies that illustrate how deep learning can solve complex problems, making it invaluable for both students and professionals seeking practical knowledge in the field.
Expert Insights
Authored by leading experts in machine learning, this hardcover edition ensures readers receive top-quality analysis and insights, enhancing its value as a trusted resource for mastering deep learning.
Product Details
- Comprehensive introduction to deep learning covering mathematical and conceptual background
- Includes deep learning techniques used in industry and research perspectives
- Describes a broad range of topics in deep learning, including mathematical and conceptual background
- Covers deep learning techniques like deep feedforward networks, regularization, convolutional networks
- Explores applications in natural language processing, speech recognition, computer vision, and more
- Suitable for undergraduate or graduate students, and software engineers wanting to utilize deep learning
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | November, 2016 |
| Pages | 800 |
| Reading level | Professional & Vocational, 18 |
| Age range | 18 Years & Up |
| Subgenre | Artificial Intelligence |
| Series title | Adaptive Computation and Machine Learning |
| Edition | 1 |
| Publisher | MIT Press |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Awards won | None |
| Is collectible | N |
| Editor | Francis Bach |
| Binding type | Case Binding |
| Retail packaging | Single Piece |
| Assembled product height | 9.1 in |
| Assembled product weight | 2.8 lb (1.27 kg) |
| Bisac subject heading | Computers |
| Package Weight | 2.6 Pound |
Who Should Buy?
-
Data Scientists
Ideal for data scientists seeking to deepen their understanding of adaptive algorithms and neural networks.
-
Graduate Students
Suitable for graduate students studying machine learning, providing advanced theoretical and practical knowledge.
-
Research Professionals
Beneficial for researchers wanting to explore the latest advancements in deep learning techniques and methodologies.
-
Beginners
May be too complex for beginners lacking foundational knowledge in machine learning and statistics.
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Ian Goodfellow All Books Editorial Review
Adaptive Computation and Machine Learning Deep Learning, a hardcover book published by MIT Press, is an essential resource for anyone keen on deep learning, combining well-explained content with professional depth. The book features 800 pages of insightful information, making it a comprehensive guide in the realm of artificial intelligence. Reviewers commend its quality, noting very good print and paper quality, and ease of understanding, despite mentioning some minor concerns regarding binding. The explicit focus on technology and non-fiction makes it a perfect fit for professionals and vocational readers aged 18 and up. This classic textbook is highly recommended for those seeking a thorough exploration of deep learning.
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Pros
- High-quality print and paper materials
- Comprehensive content on deep learning
- Easy to understand for all readers
- Recommended by multiple reviewers
- Well-explained concepts throughout
Cons
- Binding quality could be improved slightly
Product Price History
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Features & Benefits
- Comprehensive book on deep learning
- Covers mathematical and conceptual background
- Describes deep learning techniques used in industry
- Surveys various applications of deep learning
- Offers research perspectives on deep learning
- Suitable for students and software engineers
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