Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách Deep Learning Foundations and Concepts (Sách keo gáy, bìa mềm)
Deep Learning: Foundations and Concepts aims to
offer both newcomers to machine learning and those already experienced
in the field a comprehensive grasp of fundamental ideas underpinning
deep learning. Covering key concepts related to contemporary deep
learning architectures and techniques, this essential book will equip
readers with a robust foundation for potential future specialization.
The field of deep learning is undergoing rapid evolution. Rather than
summarizing the latest research developments, Bishop distills the key
ideas in order to ensure that the foundations and concepts presented in
this book will endure the test of time. For enhanced accessibility, the
book is organized into numerous bite-sized chapters, each exploring a
distinct topic. The narrative follows a linear progression, with each
chapter building upon content from its predecessors. This structure
lends itself effectively to teaching a two-semester undergraduate or
postgraduate machine learning course, while remaining equally relevant
to those engaged in active research or in self-study. To fully grasp
machine learning, a certain level of mathematical understanding is
required. The book provides a self-contained introduction to probability
theory, and includes appendices summarizing useful results in linear
algebra, calculus of variations, and Lagrange multipliers. However, the
focus of the book is on conveying a clear understanding of ideas rather
than mathematical rigor, with emphasis on real-world practical value of
techniques rather than abstract theory. Complex concepts are presented
from multiple perspectives including textual descriptions, diagrams,
mathematical formulae, and pseudo-code to cater to readers from diverse
backgrounds. This book can be viewed as a successor to Neural Networks
for Pattern Recognition (Bishop, 1995a) which provided the first
comprehensive treatment of neural networks from a statistical
perspective. It can be considered as a companion volume to Pattern
Recognition and Machine Learning (Bishop, 2006) which covered a broader
range of topics in machine learning but predates the deep learning
revolution.
Categories:Computers - Artificial Intelligence (AI)
Year:2023
Language:english
Pages:669
