Machine Learning and Artificial Intelligence Technologies for Data Science
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 362
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue focuses on practical applications of Machine Learning and Artificial Intelligence within the field of Data Science. As data availability continues to grow, data-driven Machine Learning and Artificial Intelligence methods continue to advance in terms of applicability and efficacy. They are the foundation of a wide range of processes, such as data exploration, feature engineering, computational modelling, prediction and classification.
This issue will highlight recent progress in these core areas, with an emphasis on contributions demonstrating practical value rather than purely theoretical developments. We welcome research showcasing novel algorithms, frameworks and tools that address real-world data challenges across multiple domains such as healthcare and marine technologies.
We welcome work involving time-series analysis, clustering, pattern recognition and large-scale data mining. Submissions incorporating deep learning, explainable Artificial Intelligence and generative models are also encouraged. By drawing together applied methodologies from diverse areas, this Special Issue aims to provide a comprehensive view of the current research landscape in data science.
Dr. Jacob Laurence Newman
Guest Editor
Manuscript Submission Information
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Keywords
- machine learning
- artificial intelligence
- deep neural networks
- time-series analysis
- clustering
- data mining
- generative artificial intelligence
- big data
- predictive modelling
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