£64.99
£64.99
Explore AI fundamentals with this structured guide, aligned with Indian university syllabi. It bridges conceptual learning with practical applications in robotics, healthcare, and industry, covering machine learning, intelligent agents, and ethical challenges.
This book offers a structured and pedagogically grounded exploration of AI fundamentals, aligned with Indian university syllabi. The objective is to bridge conceptual learning with practical applications across diverse domains such as robotics, education, healthcare, and industry. The book responds to a critical educational need for integrated AI resources that blend theory, algorithms, and real-world use cases within an accessible academic format. Using a combination of analytical exposition, conceptual modelling, and case-based discussion, the methodology spans literature synthesis, comparative algorithm analysis, and simplified visual representation for pedagogical clarity. Key themes include intelligent agents, search techniques, knowledge representation, and machine learning paradigms. The book’s contribution lies in its curriculum-mapped design, making it suitable for students, educators, and entry-level researchers. While limited in deep mathematical proofs, the book emphasizes clarity and comprehension over abstraction. It also identifies practical and ethical challenges associated with AI integration. Ultimately, the book advances both academic understanding and practice by contextualizing AI as a transformative tool for intelligent problem-solving, autonomous decision-making, and interdisciplinary innovation. It provides a strong foundation for future research and responsible implementation in the digital age.
This book explores the latest research in education design for virtual and augmented reality. Using numerous studies and examples, it will help the reader gain a better understanding of the nature of these realities and their applications in theory and practice.
This book shows how artificial intelligence (AI) and machine learning (ML) are used to prevent security assaults on blockchain. It explores use cases and security methods, arguing that integrating AI and ML is crucial for increasing blockchain security.
This multidisciplinary book explores COVID-19’s impact across the sciences and humanities. It offers varied perspectives on the pandemic’s challenges and solutions, with a specific focus on Indonesia. For researchers, students, the public, and policy makers.
Satellite images often suffer from interpretability issues and lost details due to sensor limitations. This book exploits deep learning to boost minute details and improve classification, showing how super-resolution improves spatial detail for precise decision-making.
This volume presents research merging classical measurement theory with modern data science. Discover novel methods for superior measurement design, robust data evaluation, and efficient instrumentation implementations.
This book offers an integral view of human speech behavior, uniting biology, linguistics, math, and AI. It explores neural networks and microelectronics for speech recognition, text-to-speech synthesis, and dialogue systems. For a broad professional audience.
This book explores how artificial intelligence (AI) interprets behavioral patterns and their influence on personality. It discusses AI’s uses, from controlling diseases to modern personality analysis, and its challenges. Perfect for data scientists, academics, and students.
Using real-world cases, this book illustrates how to handle volatile financial time series data. Learn to apply statistical, machine learning, and deep learning techniques with R and Python to build robust predictive models and construct profitable investment portfolios.
This book explores artificial intelligence through the unique lens of art, showing how we can engage with AI without being subjugated by it. Each chapter begins with a work of art to guide the reader through philosophical keywords like “author,” “memory,” and “human.”
This book is a precise and comprehensive history of the digital computer, tracing its roots and routes through the modern era. Though dealing with the history of technology in general, its central focus is the automatic digital program-controlled calculating devices of 1935-1945.
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