Còn hàng
Understanding Deep Learning
Understanding Deep Learning
Understanding Deep Learning
Understanding Deep Learning
Understanding Deep Learning
Understanding Deep Learning
Understanding Deep Learning

Understanding Deep Learning

Tình trạng: Còn hàng
Tác giả: The MIT Press
Loại: Artificial Intelligence

Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts.

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📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT954
📒 Nhà xuất bản : The MIT Press (December 5, 2023)
📒 Tác giả :  Simon J.D. Prince
📒 Ngôn ngữ :   Tiếng Anh
📒 ISBN      : 0262048647
📒 Số trang :  544  trang
📒 Hình thức : Bìa Mềm, IN ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.


📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form.

 

From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.

  • Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models
  • Short, focused chapters progress in complexity, easing students into difficult concepts
  • Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models
  • Streamlined presentation separates critical ideas from background context and extraneous detail
  • Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible
  • Programming exercises offered in accompanying Python Notebooks

📒 2. Tác giả

Simon J. D. Prince is Honorary Professor of Computer Science at the University of Bath and author of Computer Vision: Models, Learning and Inference. A research scientist specializing in artificial intelligence and deep learning, he has led teams of research scientists in academia and industry at Anthropics Technologies Ltd, Borealis AI, and elsewhere.

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