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Authors: Vemula Jasmine Sowmya, Dr Burada Sreedhar, K Vinod Kumar Reddy , Dr RadhaKrishna Karne,

Data Mining and Predictive Analytics with Artificial Intelligence explores the integration of AI techniques with data mining to discover hidden patterns, extract valuable insights, and build predictive models from large datasets. It covers machine learning algorithms, data preprocessing, classification, clustering, association rule mining, regression, and deep learning approaches for accurate forecasting and intelligent decision-making. The subject emphasizes real-world applications in healthcare, finance, business, cybersecurity, manufacturing, and smart systems, enabling organizations to make data-driven decisions and improve operational efficiency.

Authors: Dr. Aparna Joshi,Dr.Sivananda Lahari Reddy,Dr.Mohebbanaaz,Dr.Pannangi Naresh

Smart Engineering Systems with Applied AI provides a comprehensive exploration of how Artificial Intelligence (AI) is transforming traditional engineering systems into intelligent, adaptive, and autonomous solutions. The book focuses on the practical implementation of AI technologies—including machine learning, deep learning, computer vision, natural language processing, reinforcement learning, and intelligent optimization—to improve the performance, reliability, efficiency, and sustainability of engineering systems.

Authors: Dr.K.Suneel Kumar,Mr.Yalavarthi Leelakrishna,Mr.Koppisetty R M C Sekhar,Mr.Ahamad Sharif Shaik

AI System Engineering: Principles and Deployment provides a comprehensive guide to designing, developing, deploying, and maintaining Artificial Intelligence (AI)-enabled engineering systems. The book combines the theoretical foundations of AI with engineering best practices, enabling readers to understand the complete lifecycle of AI systems—from problem formulation and data preparation to model development, validation, deployment, monitoring, and continuous improvement.

Authors: Dr.Yelisela Rajesh,Rajesh Tulasi,Dr. Satish Kumar Satti,Dr.Kuncham Sreenivasa Rao

Artificial Intelligence in Engineering Applications provides a comprehensive and application-oriented exploration of how Artificial Intelligence (AI) is transforming engineering across multiple disciplines. The book demonstrates how AI techniques—including machine learning, deep learning, computer vision, natural language processing, expert systems, reinforcement learning, and intelligent optimization—are being applied to solve complex engineering problems, improve operational efficiency, and accelerate technological innovation.

Authors: Dr.Ramdas Vankdothu ,Dr.Banothu Naresh ,Mr.Pampati Nagaraju ,Dr.B.Prashanth

Principles of Artificial Intelligence Engineering provides a comprehensive introduction to the core principles, methodologies, and engineering practices required to design, develop, deploy, and manage Artificial Intelligence (AI)-based systems. The book bridges the gap between AI theory and engineering implementation, offering readers a structured understanding of how intelligent algorithms are integrated into modern engineering solutions.

Authors: Dr.B.Narsimha,Dr.G.Sathish Kumar,Dr.A.Chakradhar,Dr.Kiran Kumar M

Engineering in the Age of Artificial Intelligence explores how Artificial Intelligence (AI) is reshaping the engineering profession by transforming the way systems are designed, developed, operated, and maintained. The book provides a multidisciplinary perspective on the integration of AI into engineering, highlighting how intelligent technologies are driving innovation, automation, sustainability, and digital transformation across industries.

Authors: DR.Manikyam Sandeep,Dr.Katukojwala Praveen Kumar,Dr.V.Sree Ranganayaki

Advanced Artificial Intelligence Engineering Architectures provides an in-depth exploration of the architectural principles, frameworks, and technologies used to design, develop, deploy, and scale next-generation Artificial Intelligence (AI) systems. The book focuses on engineering robust, intelligent, and scalable AI architectures that integrate machine learning, deep learning, cloud computing, edge AI, distributed systems, and intelligent automation for real-world industrial and engineering applications.

Authors: Dr.K.B.S.D.Sarma,Bonam Srirama Durga Lakshmi,Mrs.Santhi Chilla,L.Prasanna Devarakonda

Artificial Intelligence: Principles, Architectures, and Intelligent Systems provides a comprehensive and in-depth exploration of the theoretical foundations, architectural frameworks, and practical implementation of Artificial Intelligence (AI). The book presents a balanced approach that combines AI principles with modern system architectures, enabling readers to understand how intelligent systems are designed, developed, deployed, and managed across a wide range of applications.