Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
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Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.
Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Nº de artículo: 18006456

Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)

89% of respondents would recommend this to a friend

Nº de artículo: 18006456

USD 69

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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.

Detalles de producto

Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
  • 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
Package Weight2.6 Pound

Who Should Buy?

Suitable For
  • 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.

Not Suitable For
  • Beginners

    May be too complex for beginners lacking foundational knowledge in machine learning and statistics.

DESCRIPCIÓN DEL PRODUCTO

Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)

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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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ventajas

  • 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

Contras

  • Binding quality could be improved slightly

Product Price History

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USD 69

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características y beneficios

  • 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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