Siddesh G M – författare

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solution using cloud. It includes the fundamentals of neural networks, different types and how they can be used for the multi-modal information analytics. The various application areas that are image-centric and videos are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering convolutional Neural Networks, recurrremt neural networks, and types of learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

This comprehensive work surveys the challenges, the best practices in the industry, and the latest developments and technologies. It covers the fundamentals of cloud computing, including deployment models, service models, and the benefits of cloud computing, followed by critical aspects of cloud security, including risk management, threat analysis, data protection, identity and access management, and compliance. Cloud Security explores the latest security technologies, such as encryption, multi‑factor authentication, and intrusion detection and prevention systems, and their roles in securing the cloud environment.Features:Introduces a user-centric measure of cyber security and provides a comparative study on different methodologies used for cyber securityOffers real-world case studies and hands-on exercises to give a practical understanding of cloud securityIncludes the legal and ethical issues, including the impact of international regulations on cloud securityCovers fully automated run-time security and vulnerability managementDiscusses related concepts to provide context, such as Cyber Crime, Password Authentication, Smart Phone Security with examplesThis book is aimed at postgraduate students, professionals, and academic researchers working in the fields of computer science and cloud computing.

This comprehensive work surveys the challenges, the best practices in the industry, and the latest developments and technologies. It covers the fundamentals of cloud computing, including deployment models, service models, and the benefits of cloud computing, followed by critical aspects of cloud security, including risk management, threat analysis, data protection, identity and access management, and compliance. Cloud Security explores the latest security technologies, such as encryption, multi‑factor authentication, and intrusion detection and prevention systems, and their roles in securing the cloud environment.Features:Introduces a user-centric measure of cyber security and provides a comparative study on different methodologies used for cyber securityOffers real-world case studies and hands-on exercises to give a practical understanding of cloud securityIncludes the legal and ethical issues, including the impact of international regulations on cloud securityCovers fully automated run-time security and vulnerability managementDiscusses related concepts to provide context, such as Cyber Crime, Password Authentication, Smart Phone Security with examplesThis book is aimed at postgraduate students, professionals, and academic researchers working in the fields of computer science and cloud computing.

Introduction to Generative AI: Theoretical Foundations, Analysis and Practical Use CasesGenerative Artificial Intelligence is reshaping how we create, learn, and imagine.This book offers a clear and complete journey through the science and art behind this revolution — from how machines learn to produce text, images, and music, to how they are being built, tested, and applied in the real world.The first part of the book lays out the ideas that make generative AI possible — neural networks, transformers, diffusion models, and the mysterious “latent spaces” where creativity meets computation. The middle chapters explore how today’s AI systems reason, plan, and use tools, drawing on powerful frameworks such as LangChain, LangGraph, and AutoGen. The final section moves beyond algorithms, discussing how to build safe, fair, and energy-conscious AI that serves human goals rather than replacing them.Throughout, real-world examples bring the technology to life — from language models that write poetry, to multimodal systems that can paint or compose music, to intelligent agents that collaborate with humans in research, education, and design. Written in accessible language and supported by visual explanations, this book bridges deep technical ideas with human-centered understanding.HighlightsExplains the core principles of how generative models think and createShows how AI systems combine text, vision, and sound in unified waysConnects theory with hands-on applications and real-world use casesDiscusses ethics, creativity, and sustainability in the age of intelligent machinesWritten for learners, researchers, and professionals who want both clarity and depthIntroduction to Generative AI: Theoretical Foundations, Analysis and Practical Use Cases is an essential guide for anyone curious about how artificial intelligence is shaping the next chapter of human innovation.

It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples.

In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. The edited book is divided into four parts – part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare;