TY  - BOOK
AU  - Aggarwal, Charu C.
TI  - Neural networks and deep learning : : a textbook
SN  - 9783031296413
U1  - 004.032.26 
PY  - 2023///
CY  - Cham : 
PB  - Springer
KW  - Neural networks (Computer science)
KW  - Deep learning
KW  - Machine learning
KW  - Artificial intelligence
KW  - Pre-trained language models
KW  - Reinforcement learning
KW  - Recurrent neural networks
N1  - Includes bibliographical references and index
N2  - This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail
UR  - https://link.springer.com/content/pdf/bfm:978-3-031-29642-0/1
UR  - https://www.goodreads.com/book/show/143376276-neural-networks-and-deep-learning?ref=nav_sb_ss_1_13#CommunityReviews
ER  -