?This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. Normalization methods can improve the training... Læs mere
In addition, the authors suggest that proximity is a thread between retrieval constructs based on known topics, predictable relations, and types... Læs mere
This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. The early start-up can use it to work with product or prototype design requirement analysis and its design and development.
The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD.
One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology.
Since the use of ML entails understanding which techniques can be best used for specific tasks to ensure comprehensive security, the book provides an... Læs mere
This book provides both the developers and the users with an awareness of the challenges... Læs mere
This book presents high-quality research papers presented at 3rd International Conference on Sustainable and Innovative... Læs mere