Automated Machine Learning Past Present And Future
Download Automated Machine Learning Past Present And Future PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Automated Machine Learning Past Present And Future book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Automated Machine Learning
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Proceedings of Fourth International Conference on Computing and Communication Networks
This book includes selected peer-reviewed papers presented at fourth International Conference on Computing and Communication Networks (ICCCN 2024), held at Manchester Metropolitan University, UK, during 17–18 October 2024. The book covers topics of network and computing technologies, artificial intelligence and machine learning, security and privacy, communication systems, cyber physical systems, data analytics, cyber security for industry 4.0, and smart and sustainable environmental systems.
Artificial Intelligence and Machine Learning Techniques in Engineering and Management
Author: Komaragiri Srinivasa Raju
language: en
Publisher: Springer Nature
Release Date: 2025-05-21
The present book covers various facets of Artificial Intelligence, Machine Learning, and Fuzzy Logic. It includes a brief discussion on performance indicators, Classical and Advanced Machine Learning algorithms, Fuzzy logic-based modelling algorithms, Emerging Research Areas, including Blockchain, recent ML techniques, Evolutionary Algorithms, Large Language Model (LLM)-based Generative AI, the Internet of Things, Big Data, Decision Support Systems, Taguchi design of experiments, data augmentation, and Cross-Validation, and representative case studies. The appendix covers representative AI tools, data sources, books, and journals on AI. The present book can support undergraduate, postgraduate, and Ph.D. students in Artificial Intelligence, Generative Artificial Intelligence, Machine Learning, Data Sciences, Soft Computing, and Fuzzy Logic in Engineering and Management and allied fields. The proposed book has immense value in the interdisciplinary and cross-disciplinary context.