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Artigo n.º:
104271379
Deep Learning (Adaptive Computation and Machine Learning series)
86% of respondents would recommend this to a friend
Artigo n.º:
104271379
STD 2969430
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Os nossos principais Parceiros Logísticos
“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” — Elon Musk
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O que se Destaca
Comprehensive Coverage
This book provides an in-depth exploration of deep learning concepts, catering to both beginners and advanced practitioners, ensuring a thorough understanding of the subject matter.
Cutting-Edge Techniques
It includes the latest advancements in algorithms and methodologies, equipping readers with the tools to tackle real-world challenges and stay relevant in a rapidly evolving field.
Practical Applications
The text emphasizes practical use cases, helping readers connect theory with implementation, which enhances learning and encourages innovation in solving complex problems using deep learning.
Detalhes do produto
- Comprehensive introduction to deep learning
- Covers mathematical and conceptual background
- Describes deep learning techniques used in industry
- Surveys applications in natural language processing, computer vision, and more
- Offers research perspectives on theoretical topics in deep learning
- Suitable for undergraduate and graduate students, as well as software engineers
| Publisher | The MIT Press |
| Publication date | 18 Nov. 2016 |
| Language | English |
| Print length | 800 pages |
| ISBN-10 | 0262035618 |
| ISBN-13 | 978-0262035613 |
| Reading age | 18 years and up |
| Dimensions | 23.11 x 18.29 x 2.79 cm |
Quem Deverá Comprar?
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Aspiring Data Scientists
Ideal for those looking to build foundational knowledge in deep learning and its applications in data science.
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Researchers in AI
Beneficial for advanced researchers seeking comprehensive insights and techniques in deep learning methodologies.
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Engineering Students
Suitable for engineering students focusing on artificial intelligence and machine learning technologies in their studies.
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Casual Learners
Not suitable for casual readers without a technical background who seek an overview rather than in-depth knowledge.
DESCRIÇÃO DO PRODUTO
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Perguntas e respostas do cliente
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Pergunta:
Who authored the book?
Resposta: The book is written by three experts in the field of deep learning. -
Pergunta:
What topics does the book cover?
Resposta: It covers mathematical concepts, deep learning techniques, and practical applications across various industries. -
Pergunta:
Is this book suitable for beginners?
Resposta: Yes, it is suitable for undergraduate and graduate students, as well as software engineers new to deep learning.
Revisão editorial
**** The book "Deep Learning," part of the Adaptive Computation and Machine Learning series, has garnered attention for its comprehensive treatment of the subject despite some criticisms regarding its mathematical rigor. The authors, recognized as leading figures in the field, offer insights that blend practical applications with the theoretical underpinnings of deep learning. Reviewers appreciate the emphasis on real-world applicability, noting that the book steers clear of excessive mathematical abstractions that often obscurate practical understanding. Instead, it focuses on actionable insights crucial for practitioners in areas like image and speech recognition. Readers have highlighted the extensive and relevant literature provided, which enhances the reader's ability to delve deeper into specific topics of interest without necessitating prior comprehension of all referenced materials. However, while the book excels in providing a robust overview and practical advice—especially beneficial for both novices and experienced practitioners—it has been noted that some sections may lack the in-depth theoretical formulations expected in a scientific text. Some customers indicate that while the book is an excellent resource for those looking to understand deep learning concepts deeply, it may not fully equip one for the complexities found in advanced academic literature. Moreover, a solid foundation in mathematics, particularly linear algebra and numerical calculus, is highly suggested for optimal comprehension. Overall, the book receives high praise for its clarity, depth, and practical orientation, making it a valuable addition for anyone keen on mastering deep learning techniques. **
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Prós
- Comprehensive and up-to-date overview of deep learning.
- Strong emphasis on practical applications over purely theoretical concepts.
- Valuable insights from leading experts in the field.
- Extensive literature for further study is included.
- Suitable for both beginners and experienced practitioners.
Contras
- Some chapters may lack solid mathematical formulation.
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STD 2969430
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Em conformidade com a norma PCI DSS e com certificação ISO 27001:2022, com pagamentos encriptados e proteção total do comprador em todas as encomendas.
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Recursos e benefícios
- Comprehensive introduction to deep learning.
- Covers mathematical and conceptual foundations.
- Includes industry techniques like convolutional networks.
- Surveys applications in NLP, speech recognition, and more.
- Suitable for undergraduate, graduate, and software engineers.
- Supplementary materials available online.
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