This book explains different applications of supervised and unsupervised data engineering for working with multimedia objects. Throughout this book, the contributors highlight the use of Artificial Intelligence-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, automation in vehicle manufacturing, data science and automation in electronics industries. The book presents seven chapters which present use-cases for AI engineering that can be applied in many fields. The book concludes with a final chapter that summarizes emerging AI trends in intelligent and interactive multimedia systems. Key features: - A concise yet diverse range of AI applications for multimedia data engineering - Covers both supervised and unsupervised machine learning techniques - Summarizes emerging AI trends in data engineering - Simple structured chapters for quick reference and easy understanding - References for advanced readers This book is a primary reference for data science and engineering students, researchers and academicians who need a quick and practical understanding of AI supplications in multimedia analysis for undertaking or designing courses. It also serves as a secondary reference for IT and AI engineers and enthusiasts who want to grasp advanced applications of the basic machine learning techniques in everyday applications.

Basics of Python Programming: A Quick Guide for Beginners is an essential companion to mastering the Python programming language. The book presents information about Python in 12 structured chapters with a strong emphasis on fundamentals and practical information. Starting with basic operators, functions and expressions, contents explain file handling, exception handling and modules. The book concludes with advanced topics such as object oriented programming and machine learning. Key Features: Fundamental Focus: Covers the core concepts of Python programming to build a strong foundation in python programming in an easy-to-understand format. Practical Demonstrations: Learn by doing. This textbook includes hands-on practical demonstrations that reinforce your understanding of Python concepts. IDE Guidance: Includes programming and installation guidance for Python-supporting Integrated Development Environments (IDEs). Explores Python Frameworks: Introduces Python frameworks such as Matplotlib, TensorFlow, PyTorch, Scikit-Learn, and NLTK for complex projects. Python for Machine Learning: Gives a preliminary understanding of Python for machine learning tasks for data science and AI applications. Basics of Python Programming: A Quick Guide for Beginners is the perfect starting point for aspiring students, programmers and tech enthusiasts. Whether you're a student looking to build a solid foundation in Python or an industry professional venturing into machine learning and artificial intelligence, this textbook has you covered.

This volume reviews cutting-edge innovations in blockchain technology that are propelling the healthcare industry into a new era of efficiency and security. It brings 14 reviews contributed by experts in blockchain and Web3 technologies into a single volume. Each contribution includes a summary for easy understanding and scientific references for advanced readers. Key Themes: Empowering Decentralized Healthcare: Learn about the future of decentralized healthcare, powered by blockchain, ensuring a seamless and patient-centric experience. Clinical Trials: Discover how blockchain is reshaping clinical trials, offering a glimpse into a future of optimized medical research. Data Security: Uncover the strategic use of blockchain in securing vital clinical trials data, ensuring confidentiality and integrity at every step. Blockchain-based Healthcare delivery: Delve into a comprehensive review of blockchain technology in the health sector, revealing its potential to transform healthcare systems with efficient and precise solutions. Predict, Prevent, and Protect: Understand how blockchain technology serves as a predictive tool, aiding in the prevention and control of the spread of COVID-19. This volume is a must-read for healthcare practitioners and administrators seeking to harness the power of blockchain in medicine and healthcare. It also provides information for researchers and business professionals who want to understand the innovative role of blockchain technology in the healthcare sector.

Artificial Intelligence and Knowledge Processing: Methods and Applications demonstrates the transformative power of Artificial Intelligence (AI) in our lives. The book is a collection of 14 edited reviews that cover a wide range of topics showcasing the application of AI and machine learning to create knowledge, and facilitate different processes. The book starts by illuminating how AI is employed in robotics, IoT, marketing, and operations. It showcases how AI extracts insights from big data, optimizes museum management, and empowers automated garden path planning using reinforcement learning. The book also explores how AI can be used to predict heart disease using artificial neural networks. Furthermore, the book underscores how AI predicts crop suitability, manages crop systems, and can even help to detect violence in using computer vision. Chapters highlight specific techniques or systems such as recommendation systems and reinforcement learning where appropriate. Key Features: · Showcases a wide range of AI applications · Bridges theory and practice with real-word insights · Uses accessible language to explain complex AI concepts · Includes references for advanced readers This book is intended as a guide for a broad range of readers who want to learn about AI applications and the profound influence it has on our lives.

Artificial Intelligence (AI) is an interdisciplinary science with multiple approaches to solve a problem. Advancements in machine learning (ML) and deep learning are creating a paradigm shift in virtually every tech industry sector. This handbook provides a quick introduction to concepts in AI and ML. The sequence of the book contents has been set in a way to make it easy for students and teachers to understand relevant concepts with a practical orientation. This book starts with an introduction to AI/ML and its applications. Subsequent chapters cover predictions using ML, and focused information about AI/ML algorithms for different industries (health care, agriculture, autonomous driving, image classification and segmentation, SEO, smart gadgets and security). Each industry use-case demonstrates a specific aspect of AI/ML techniques that can be used to create pipelines for technical solutions such as data processing, object detection, classification and more. Additional features of the book include a summary and references in every chapter, and several full-color images to visualize concepts for easy understanding. It is an ideal handbook for both students and instructors in undergraduate level courses in artificial intelligence, data science, engineering and computer science who are required to understand AI/ML in a practical context.

Amazon Web Services: A Comprehensive Guide for Beginners and Advanced Users is your go-to companion for learning and mastering AWS. It presents 10 easy-to-read chapters that build a foundation for cloud computing while also equipping readers with the skills necessary to use AWS for commercial projects. Readers will learn how to use AWS cloud computing services for seamless integrations, effective monitoring, and optimizing cloud-based web applications. What you will learn from this guide: 1. Identity and Access Management in AWS: Learn about IAM roles, security of the root account, and password policies, ensuring a robust foundation in access management. 2. Amazon EC2 Instance: Explore the different types of EC2 instances, pricing strategies, and hands-on experiences to launch, manage, and terminate EC2 instances effectively. This knowledge will help to make informed choices about pricing strategies. 3. Storage Options and Solutions: A detailed examination of storage options within Amazon EC2 instances. Understanding Amazon Elastic Block Store (EBS), Amazon Elastic File Storage (EFS), and more, will enhance your ability to handle data storage efficiently. 4. Load Balancing and Auto Scaling: Learn about different types of load balancers and how auto-scaling groups operate, to master the art of managing varying workloads effectively. 5. Amazon Simple Storage Service (S3): Understand S3 concepts such as buckets, objects, versioning, storage classes, and practical applications. 6. AWS Databases and Analytics: Gain insights into modern databases, AWS cloud databases, and analytics services such as Amazon Quicksight, AWS Glue, and Amazon Redshift. 7. Compute Services and Integrations: Understand the workings of Docker, virtual machines, and various compute services offered by AWS, including AWS Lambda and Amazon Lightsail, Amazon MQ and Amazon SQS. 8. Cloud Monitoring: Understand how to set up alarms, analyze metrics, and ensure the efficient monitoring of your cloud environment using Amazon CloudWatch and CloudTrail. Key Features: Comprehensive Introduction to Cloud Computing and AWS Guides readers to the complete set of features in AWS Easy-to-understand language and presentation with diagrams and navigation guides References for further reading Whether you're a student diving into cloud specialization as part of your academic curriculum or a professional seeking to enhance your skills, this guide provides a solid foundation for learning the potential of the AWS suite of applications to deploy cloud computing projects.

This book explores the dynamic intersection of three cutting-edge technologies—Artificial Intelligence (AI), Internet of Things (IoT), and Cloud Computing—and their profound impact on diverse domains. Beginning with an introduction to AI and its challenges, it delves into IoT applications in fields like transportation, industry 4.0, healthcare, and agriculture. The subsequent chapter explores AI in the cloud, covering areas such as banking, e-commerce, smart cities, healthcare, and robotics. Another section investigates the integration of AI and IoT-Cloud, discussing applications like smart meters, smart cities, smart agriculture, smart healthcare, and smart industry. Challenges like data privacy and security are examined, and the future direction of these technologies, including fog computing and quantum computing, is explored. The book concludes with use cases that highlight the real-world applications of these transformative technologies across various sectors. Each chapter is also supplemented with a list of scholarly references for advanced readers. The book is intended primarily as a resource for students in information technology and technology courses. And as a secondary resource for industry professionals who want to learn about these technologies in the context of digital transformation.

Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting. Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis. Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity. Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture. Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities. Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments. Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face. Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis. Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data. Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics. This volume bridges the gap between data science and interdisciplinary research, making it a valuable resource for researchers, academics, and professionals seeking to leverage cutting-edge technologies for transformative applications.

Reinventing Technological Innovations with Artificial Intelligence delves into the transformative impact of Augmented and Virtual Reality (AVR) technology across industries. The book explores the merging of real and digital worlds, paving the way for personalized experiences in areas such as tourism, marketing, education, and more. With the potential to redefine business practices and societal norms in the era of Industry 4.0, AVR technologies hold untapped potential beyond gaming and entertainment. This volume presents a comprehensive overview of the current landscape, challenges, and prospects of integrating AVR with Artificial Intelligence (AI) for innovation and sustainability in various domains. The book presents 11 edited chapters contributed by technology and innovation experts that explore applications of AI, AR and VR technologies in different sectors in both public and private sectors. The editors have included reviews of technologies that impact human resource management, corporate social responsibility, healthcare, supply chain and criminal investigation. The reviews also highlight the role of AI in sustainable agriculture and smart cities. Key Features: Unveils the role of AVR in transforming real surroundings into digitally enhanced personal experiences. Explores AVR's applications beyond gaming in diverse sectors like marketing, construction, education, and more. Discusses challenges such as technical limitations, high costs, and resistance to adopting AVR. Addresses the need to enhance the reliability and effectiveness of AVR technologies in various industries. Provides a comprehensive perspective on AI innovations, AR, and VR technologies with real-world examples. The book is an informative reference for researchers, professionals, and experts in technology, innovation, who are interested in the convergence of Augmented and Virtual Reality with AI for practical applications in diverse industries.

Marvels of Artificial and Computational Intelligence in Life Sciences is a primer for scholars and students who are interested in the applications of artificial intelligence (AI) and computational intelligence (CI) in life sciences and other industries. The book consists of 16 chapters (9 of which focus on AI and 7 of which showcase the benefits of CI approaches to solve specific problems). Chapters are edited by subject experts who describe the roles and applications of AI and CI in different parts of our lives in a concise and lucid manner. The book covers the following key themes: AI Revolution in Healthcare and Drug Discovery: AI's Impact on Biology and Energy Management AI and CI in Physical Sciences and Predictive Modeling Computational Biology The editors have compiled a good blend of topics in applied science and engineering to give readers a clear understanding of the multidisciplinary nature of the two facets of computing. Each chapter includes references for advanced readers.