Transformers for Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
by Uday Kamath, Kenneth Graham, Wael Emara
An introduction to transformer models and their applications in machine learning and pattern recognition, guiding readers through core concepts and implementation strategies.
About This Book
This book introduces transformer architectures and their role in modern machine learning.
Readers explore core concepts of attention mechanisms and sequence modeling.
The text covers implementation considerations within established pattern recognition frameworks.
Emphasis is placed on practical integration of transformers into existing machine learning workflows.
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