Computational Methods for Deep Learning

Name: Computational Methods for Deep Learning
Price: 165.78 AUD
Availability: OutOfStock
ISBN: 9789819948222

Theory, Algorithms, and Implementations

Wei Qi Yan

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Hardback

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English

Springer Verlag, Singapore
16 September 2023

Mathematical modelling; Maths for computer scientists; Artificial intelligence; Machine learning; Image processing

Series: Texts in Computer Science

The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book.

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.

By: Wei Qi Yan
Imprint: Springer Verlag, Singapore
Country of Publication: Singapore
Edition: 2nd ed. 2023
Dimensions: Height: 235mm, Width: 155mm,
Weight: 535g
ISBN: 9789819948222
ISBN 10: 9819948223
Series: Texts in Computer Science
Pages: 222
Publication Date: 16 September 2023
Audience: Primary & secondary/elementary & high school , Children's (6-12)
Format: Hardback
Publisher's Status: Active

1. Introduction.- 2. Deep Learning Platforms.- 3. CNN and RNN.- 4. Autoencoder and GAN.- 5. Reinforcement Learning.- 6. CapsNet and Manifold Learning.- 7. Boltzmann Machines.- 8. Transfer Learning and Ensemble Learning.

Wei Qi Yan is Director of Institute of Robotics & Vision (IoRV) at Auckland University of Technology (AUT) in New Zealand (NZ). Dr. Yan's research interests encompass deep learning, intelligent surveillance, computer vision, and multimedia computing. His expertise lies in computational mathematics, applied mathematics, computer science, and computer engineering. He holds the positions of Chief Technology Officer (CTO) of Screen 2 Script Limited (NZ) and Director and Chief Scientist of the Joint Laboratory between AUT and Shandong Academy of Sciences China (NZ). Dr. Yan also serves as Chair of ACM Multimedia Chapter of New Zealand and is Member of the ACM. Additionally, he is Senior Member of the IEEE and TC Member of the IEEE. In 2022, Dr. Yan was recognized as one of the world’s top 2% cited scientists by Stanford University.