Understanding Deep Learning by Simon J.D. Prince (ISBN 9780262048644) - Hardcover

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  • Condition: Brand New,
  • Author: Simon J.D. Prince
  • ISBN13: 9780262048644
  • ISBN10: 0262048647
  • Type: Hardcover Book.
  • Publisher: The MIT Press
  • Language : English

By: Simon J.D. Prince Availability: In Stock Condition: Brand New,

$51.99
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Understanding Deep Learning (ISBN 9780262048644)

Understanding Deep Learning by Simon J.D. Prince is one of the most comprehensive and accessible introductions to deep learning available today. Published by MIT Press, this textbook combines clarity, technical rigor, and modern perspectives, making it suitable for students, researchers, and professionals seeking a strong theoretical and practical foundation in deep learning.

Product Details

  • Title: Understanding Deep Learning
  • Author: Simon J.D. Prince
  • ISBN-13: 9780262048644
  • Format: Paperback
  • Price: $51.99
  • Minimum Order: 5 Copies
  • Availability: In Stock | Free Shipping

About This Book

This textbook offers a complete, modern introduction to deep learning, balancing mathematical depth with real-world intuition. Prince demystifies neural networks, optimization methods, generative modeling, and the underlying principles that drive today’s most powerful AI systems. The book requires only basic linear algebra and probability, making it accessible while still deeply informative.

Key Features

  • Clear Mathematical Foundations: Step-by-step explanations of core concepts without assuming advanced math background.
  • Modern Deep Learning Coverage: Includes transformers, convolutional networks, optimization, and generative models.
  • Intuitive Visualizations: Hundreds of diagrams and explanations to illustrate complex ideas.
  • Practical Insight: Focuses on why methods work—not just how.
  • Research-Aligned: Bridges theory with the latest developments in AI.

Topics Covered

  1. Foundations of Neural Networks
  2. Optimization and Training Dynamics
  3. Convolutional Networks and Vision Models
  4. Transformers and Attention Mechanisms
  5. Autoencoders and Generative Models
  6. Regularization, Generalization, and Overfitting
  7. Probabilistic Models and Uncertainty
  8. Deep Learning Applications Across Domains

Who This Book Is For

  • Students in computer science, data science, and engineering
  • Researchers entering machine learning or AI
  • Machine learning practitioners
  • Software engineers transitioning into AI roles
  • Instructors building deep learning courses

Why Buy from BooksGoat?

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  • Minimum order of 5 copies for classrooms, bootcamps, and training programs
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Final Call – Order Now

Understanding Deep Learning is a must-have reference for anyone serious about mastering modern AI. Order your minimum of 5 copies today with free shipping.