Applications of Data Analytics, Machine Learning, AI and Mathematical Optimization Principles
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There is no doubt that the various needs of our modern world, comes with increase in the importance of data, increase in the amount of data, an increase in the variety of data, and increase in diverse data-driven technologies. Modern technologies such as Artificial intelligence and Machine Learning processes and applications which include processes to save project cost and time are based on the foundation formed by Data Science, Data Analytics, Mathematics and its principles that contributes to various fields and projects by software data-driven applications that can make the decision-making p...
There is no doubt that the various needs of our modern world, comes with increase in the importance of data, increase in the amount of data, an increase in the variety of data, and increase in diverse data-driven technologies. Modern technologies such as Artificial intelligence and Machine Learning processes and applications which include processes to save project cost and time are based on the foundation formed by Data Science, Data Analytics, Mathematics and its principles that contributes to various fields and projects by software data-driven applications that can make the decision-making process easier and quicker; thereby increasing value, and creating a better, more productive world. Therefore, the big questions of where, when, why and how the principles of Machine Learning, Artificial Intelligence, Analytics and Mathematical Optimization in relation to Data as applied to various fields becomes pertinent, and the evidence of case study practical applications are seen as very useful for industry and the academia. This book presents some of these important case study examples across different fields of study as an excellent background and opener to more possibilities and the great potentials of these Data, AI/ML and Mathematical principles in our data-centric, dynamic world.
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