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Introduction to Machine Learning
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and nonexpert readers in statistics, computer science, mathematics, and engineering.
Handbook of Intelligent and Sustainable Smart Dentistry
With the exponential growth of science and technology, the delivery of dental care has shifted from conventional methods to intelligent techniques. In addition to adapting intelligent techniques, sustainable dental practice is of the utmost importance. Eco-friendly dentistry, sustainable dentistry, or green dentistry are approaches that reduce the environmental impact of dental practice and help safeguard planetary and community well-being. This handbook provides the latest and most comprehensive evidence-based guidance on intelligent and sustainable approaches in dentistry. Handbook of Intelligent and Sustainable Smart Dentistry: Nature and Bio-Inspired Approaches, Processes, Materials, and...
Security and Risk Analysis for Intelligent Cloud Computing
This edited book is a compilation of scholarly articles on the latest developments in the field of AI, Blockchain, and ML/DL in cloud security. This book is designed for security and risk assessment professionals, and to help undergraduate, postgraduate students, research scholars, academicians, and technology professionals who are interested in learning practical approaches to cloud security. It covers practical strategies for assessing the security and privacy of cloud infrastructure and applications and shows how to make cloud infrastructure secure to combat threats and attacks, and prevent data breaches. The chapters are designed with a granular framework, starting with the security conc...
An Interdisciplinary Approach to Modern Network Security
An Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer n...
Advanced Data Mining Tools and Methods for Social Computing
Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. - Provides insights into the latest research trends in social network analysis - Covers a broad range of data mining tools and methods for social computing and analysis - Includes practical examples and case studies across a range of tools and methods - Features coding examples and supplementary data sets in every chapter
Sustainable Smart Homes and Buildings with Internet of Things
Written and edited by a team of experts in the field, this exciting new volume explores the real-world applications and methods for using Internet of Things (IoT) to make homes and buildings smart and sustainable and to continue working toward a “greener” world. Sustainable Smart Homes and Buildings with Internet of Things (IoT) is a book that explores the integration of renewable energy sources and IoT technology in the design and management of smart homes and buildings. The book covers various topics related to the subject, including energy efficiency, real-time monitoring, control and optimization of renewable energy sources, smart grid integration, energy storage systems, and microgr...
Intelligence Enabled Research
This book gathers extended versions of papers presented at DoSIER 2020 (the Second Doctoral Symposium on Intelligence Enabled Research, held at Visva-Bharati University, Santiniketan, West Bengal, India, during 12–13 August 2020). The papers address the rapidly expanding research area of computational intelligence, which, no longer limited to specific computational fields, has since made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design, to name but a few. Presenting chapters written by experts active in these areas, the book offers a valuable reference guide for researchers and industrial practitioners alike and inspires future studies.
Data Driven Decision Making using Analytics
This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining. Features: Covers descriptive statistics with respect to predictive analytics and business analytics. Discusses different data analytics platforms for real-time applications. Explain SMART business models. Includes algorithms in data sciences alongwith automated methods and models. Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics. This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.
Proceedings of Third International Conference on Computing and Communication Networks
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