Probing The Past With Data Analytics And Ai
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Probing The Past With Data Analytics And Ai
This comprehensive compendium explains the technical challenges and opportunities behind the most recent and successful applications in artificial intelligence [AI] and data analytics. It focuses on applications that have the power to be adapted to many different fields and explains how AI can be implemented as an assistant in digital humanities. It also introduces new methods and applications in classification trees, networks, and Bayesian learning.The useful reference text benefits professionals, academics, researchers, and graduate students in AI/machine learning, neural networks, and bioinformatics, and digital humanities.
Probing Past with Data Analytics and Ahb
Author: Marc Thuillard
language: en
Publisher: World Scientific Publishing Company
Release Date: 2025
This comprehensive compendium explains the technical challenges and opportunities behind the most recent and successful applications in artificial intelligence [AI] and data analytics. It focuses on applications that have the power to be adapted to many different fields and explains how AI can be implemented as an assistant in digital humanities. It also introduces new methods and applications in classification trees, networks, and Bayesian learning. The useful reference text benefits professionals, academics, researchers, and graduate students in AI/machine learning, neural networks, and bioinformatics, and digital humanities.
Data Science & Exploration in Artificial Intelligence
The book captures the essence of the International Conference on Data Science & Exploration in Artificial Intelligence and offers a comprehensive exploration of cutting-edge research in AI, data science, and their applications. It covers a wide array of topics including advanced Data Science, IoT, Security, Cloud Computing, Networks, Security, Image, Video and Signal Processing, Computational Biology, Computer and Information Technology. It highlights innovative research contributions and practical applications, offering readers a detailed understanding of current trends and challenges. The findings emphasize the role of global collaboration and interdisciplinary approaches in pushing the boundaries of AI and data science. Selected papers published by Taylor and Francis showcase pioneering work that is shaping the future of these fields. This is an ideal read for AI and data science researchers, industry professionals, and students seeking to stay updated on the latest advancements and ethical considerations in these areas.