000			01335 a2200205 4500
005			20260902123016.0
020			_a9789819948222
080			_a004.85 YAN
100			_aYan, Wei Qi. _94016
245			_aComputational methods for deep learning: theory, algorithms, and implementations / by Wei Qi Yan
250			_a2nd edition.
260			_aSingapore: _bSpringer Nature, _c2023.
300			_axx, 222 p. _c24 cm.
440			_aTexts in computer science _94017
520			_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.
650			_aDeep learning _94021
650			_aMachine intelligence _94019
650			_aRobotic control _94020
942			_cREF
999			_c5627 _d5622