01256    a2200181   450000500170000002000180001708000150003510000170005024501010006725000170016826000400018530000230022544000300024852007330027865000180101165000250102965000200105420260902123016.0  a9789819948222  a004.85 YAN  aYan, Wei Qi.  aComputational methods for deep learning: theory, algorithms, and implementations / by Wei Qi Yan  a2nd edition.  aSingapore:bSpringer Nature,c2023.  axx, 222 p.c24 cm.  aTexts in computer science  aThe second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). 

This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas.  aDeep learning  aMachine intelligence  aRobotic control