Deep Learning: Foundations and Concepts
This essential book equips readers with a robust foundation for potential future specialization in deep learning.
Deep Learning: Foundations and Concepts
Item #: 88850221

Deep Learning: Foundations and Concepts

Item #: 88850221

USD 107

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This essential book equips readers with a robust foundation for potential future specialization in deep learning.
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What Stands Out

Comprehensive Coverage
This hardcover edition provides an extensive understanding of deep learning, covering foundational principles and advanced concepts, making it suitable for both beginners and seasoned practitioners.
Expert Insights
Authored by leading experts in the field, this book offers valuable insights and real-world applications, helping readers grasp complex topics and stay current with the latest developments in deep learning.
Practical Examples
Includes practical examples and case studies that illustrate theoretical concepts, allowing readers to apply knowledge effectively, enhancing learning and implementation in real-world scenarios.

Product Details

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Who Should Buy?

Suitable For
  • Students and Researchers

    Ideal for students and researchers seeking a comprehensive understanding of deep learning principles and methodologies.

  • Industry Professionals

    Beneficial for professionals in tech fields looking to enhance their skills and knowledge in deep learning applications.

  • Educators

    Great for educators teaching deep learning, providing a strong foundation and detailed concepts for course material.

Not Suitable For
  • Beginners

    Not suitable for complete beginners lacking prior knowledge, as it may be too complex without foundational understanding.

Product Description

Deep Learning: Foundations and Concepts

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English edition Christopher M. Bishop Editorial Review

Deep Learning: Foundations And Concepts is a high-quality textbook that effectively teaches the fundamentals of deep learning, including probability theory and recent advancements like Transformers and autoencoders. The book is well-structured and utilizes color effectively to highlight key points, making complex information more digestible. Readers should note that a background in calculus and linear algebra is essential for fully grasping the concepts presented. The book's emphasis on critical elements over excessive detail and the provision of exercise solutions online enhance its utility for self-study. Overall, this textbook is a fantastic reference for anyone serious about exploring deep learning.

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Pros

  • Well-structured and clearly presented content
  • Covers recent advancements in deep learning
  • Utilizes color effectively for key points
  • Includes online solutions for exercises
  • Requires essential math background for understanding

Product Price History

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