Название: AI-Centric Modeling and Analytics; Concepts, Technologies, and Applications
Автор: Alex Khang, Vugar Abdullayev, Babasaheb Jadhav, Shashi Kant Gupta
Издательство: CRC Press
Год: 2024
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 30.5 MB

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, Machine Learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0.

AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries.

Machine Learning (ML) models and Deep Learning frameworks are needed to simulate large datasets and explain why clients arrive at these decisions. To make the work of AI-centric modeling and predictive analysis even more transparent, visualization graphs of business scenarios are introduced in this book. We also demonstrate how a variety of technologies can be used to integrate data fabric solutions and how intelligent applications can be used to enhance the effect of combining the six fields of AI-centric modeling, data analytics, ML-aided models, IoT-driven applications, cybersecurity techniques, and cloud-enabled platforms for developing smart business systems in the era of AI and Data Science.

AI is not only a buzzword or any special feature of Computer Science; it collaborates with other computer science areas, such as ML, Deep Learning, Big Data analytics, and natural language processing (NLP). Artificial Intelligence uses multiple programming languages and supports multiple tools to record data as well as to build an algorithm to create a model based on data. AI has three phases: assisted intelligence, where insights of data are shared with a human being to make decisions; augmented intelligence, where ML capabilities are utilized to generate the outcome; and full automation, where inputs, processes, outputs, and decision-making are taken care of by AI

Natural language processing (NLP) is an amalgamation of both technology and language. Technology encompasses computer science and artificial intelligence (AI). Language covers both text and speech. Over the generations, humans have been interacting and communicating with each other through language. The exchange of ideas occurs through speech or written text. In contrast, machines are programmed using low-level or high-level scripting. Natural language processing is a tool that enables a machine to comprehend text and language. It is used to apply Machine Learning algorithms to both text and speech. At this conjuncture, it can be stated that NLP is a subdomain of linguistics, computer science and AI.

This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.




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