Computational methods for deep learning: theory, algorithms, and implementations / by Wei Qi Yan

Yan, Wei Qi.

Computational methods for deep learning: theory, algorithms, and implementations / by Wei Qi Yan - 2nd edition. - Singapore: Springer Nature, 2023. - xx, 222 p. 24 cm. - Texts in computer science .

The 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.

9789819948222


Deep learning
Machine intelligence
Robotic control

004.85 YAN

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