Toward Artificial General Intelligence : Deep Learning, Neural Networks, Generative AI / edited by Victor Hugo C. de Albuquerque, Pethuru Raj, and Satya Prakash Yadav.

Includes index.

1: Introduction to artificial intelligence -- 2: AI technologies, tools, and industrial use cases -- 3: Classification and regression algorithms -- 4: Clustering and association algorithm -- 5: Reinforcement learning -- 6: Evaluation of AI model performance -- 7: Methods of cross-validation and bootstrapping -- 8: Meta-learning through ensemble approach: bagging, boosting, and random forest strategies -- 9: AI: issues, concerns, and ethical considerations -- 10: The future with AI and AI in action -- 11: A survey of AI in industry: from basic concepts to industrial and business applications -- 12: The intelligent implications of artificial intelligence-driven decision-making in business management -- 13: An innovative analysis of AI-powered automation techniques for business management -- 14: The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications -- 15: Utilizing AI technologies to enhance e-commerce business operations -- 16: Exploring the potential of artificial intelligence in wireless sensor networks -- 17: Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining -- 18: Exploring the potential of artificial intelligence for automated sentiment -- 19: A novel blockchain-based artificial intelligence application for healthcare automation -- 20: Enhancing industrial efficiency with AI-enabled blockchain-based solutions.

Artifi cial Intelligence (AI) has been an exciting fi eld of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry. The bookpresents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments, articulates and accentuates the most recent developments taking place in the domain of Artifi cial Intelligence, covers the noteworthy innovations and disruptions towards Generative Artifi cial Intelligence (Generative AI), explains the breakthrough innovations and disruptions towards Artifi cial General Intelligence (AGI) and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics

Description based on print version record.

Electronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.