Machine learning

Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks.

This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain.

This book includes high-quality papers presented at International Conference on Scientific and Natural Computing (SNC 2021), organized by Department of Applied Mathematics, Gautam Buddha University, Greater Noida in collaboration with IIT Roorkee and Technical University of Ostrava (VSB-TU) and technically sponsored by Soft Computing Research Society of India, held online during 5 - 6 February 2021.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience.

This book presents selected papers from the 5th International Conference on Inventive Systems and Control (ICISC 2021), held on 7-8 January 2021 at JCT College of Engineering and Technology, Coimbatore, India.

This book presents the outcome of two-day 2nd International e-Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering and Technology (ICSISCET 2020) held at Madhav Institute of Technology & Science (MITS), Gwalior, India, from December 18-19, 2020.

This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data.

This book discusses various aspects of text data mining.

The book aims to outline the issues of AI and COVID-19, involving predictions,medical support decision-making, and possible impact on human life.

Many AI (and machine learning) tasks present in dual forms, e.

This book contains high-quality peer-reviewed papers of the International Conference on Big Data, Machine Learning and their Applications (ICBMA 2019) held at Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India, during 29-31 May 2020.

This book presents applications of machine learning techniques in processing multimedia large-scale data.

This edited book provides an optimal portrayal of the principles and applications related to network security.

This book highlights reliable, valid and practical testing and assessment of interpreting, presenting important developments in China, where testing and assessment have long been a major concern for interpreting educators and researchers, but have remained largely under-reported.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience.

This book highlights selected papers from the Mechanical Engineering track, with a focus on mechatronics and manufacturing, presented at the "e;Malaysian Technical Universities Conference on Engineering and Technology"e; (MUCET 2019).

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects.

This book describes the application of vision-sensing technologies in welding processes, one of the key technologies in intelligent welding manufacturing.

This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics.

This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables.

This volume contains select papers presented during the 2nd National Conference on Multidisciplinary Analysis and Optimization.

This book presents recent advances in the field of distributed computing and machine learning, along with cutting-edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.

Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning.

The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.

This book features selected research papers presented at the First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019), organized by Northwest Group of Institutions, Punjab, India, Southern Federal University, Russia, and IAC Educational Trust, India along with KEC, Ghaziabad and ITS, College Ghaziabad as an academic partner and held on 12-13 October 2019.

This book covers applications of machine learning in artificial intelligence.

This book is a collection of outstanding papers presented at the 1st International Conference on Advances in Computational Intelligence and Informatics (ICACII 2019), organized by the Department of Computer Science & Engineering, Anurag Group of Institutions (AGI), Hyderabad, on 20-21 December 2019.

This book gathers selected research papers presented at the AICTE-sponsored International Conference on IoT Inclusive Life (ICIIL 2019), which was organized by the Department of Computer Science and Engineering, National Institute of Technical Teachers Training and Research, Chandigarh, India, on December 19-20, 2019.

This book on optimization includes forewords by Michael I.

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty.

This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications.

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics.

The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis.

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data.

This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16-17 August 2019.

Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research.

This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes.

This book advances research on mobile robot localization in unknown environments by focusing on machine-learning-based natural scene recognition.

Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research.

This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches.

This unique compendium gives an updated presentation of clustering, one of the most challenging tasks in machine learning.

The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning.

This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives - the statistical perspective, the artificial neural network perspective and the deep learning methodology.

This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning.

Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout machine learning.

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering.

Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications.

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications.