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ARTIFICIAL INTELLIGENCE MACHINE LEARNING DATA SCIENCE ENGINEERING - USAGE AND CHALLENGES
Artificial Intelligence, Machine Learning, Data Science, and Engineering are coming together to create a convergence that is transforming businesses and society at a rate that has never been seen before. A new age that is characterised by automation, predictive analytics, and decision-making that is driven by data has been born as a result of the convergence of distinct fields of study. The fast growth of technology, however, is accompanied by a number of complicated issues, including ethical considerations, the protection of data privacy, and the possibility of employment displacement.
The theoretical foundations, practical applications, and ethical implications of these interrelated domains are all thoroughly investigated in this book, which provides a comprehensive analysis of its contents. We investigate the algorithms and models that are used to fuel artificial intelligence systems, bringing to light their advantages, disadvantages, and possible biases. In addition, we investigate the role that data plays as the driving force behind these technologies, having a conversation about the collecting, management, and privacy problems associated with data. A comprehensive investigation is also conducted into the engineering problems that are involved in the process of building and deploying AI systems, with a particular emphasis placed on scalability, dependability, and security.
Our aim is to provide a comprehensive resource for researchers, practitioners, policymakers, and students who seek to understand the transformative impact of AI, ML, data science, and engineering. By elucidating both the opportunities and challenges presented by these technologies, we hope to foster informed and responsible innovation.
The theoretical foundations, practical applications, and ethical implications of these interrelated domains are all thoroughly investigated in this book, which provides a comprehensive analysis of its contents. We investigate the algorithms and models that are used to fuel artificial intelligence systems, bringing to light their advantages, disadvantages, and possible biases. In addition, we investigate the role that data plays as the driving force behind these technologies, having a conversation about the collecting, management, and privacy problems associated with data. A comprehensive investigation is also conducted into the engineering problems that are involved in the process of building and deploying AI systems, with a particular emphasis placed on scalability, dependability, and security.
Our aim is to provide a comprehensive resource for researchers, practitioners, policymakers, and students who seek to understand the transformative impact of AI, ML, data science, and engineering. By elucidating both the opportunities and challenges presented by these technologies, we hope to foster informed and responsible innovation.
300 pages, Kindle Edition
Published August 12, 2024
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