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About This Journal

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Journal of Data Sciences (JDS) is an international, peer-reviewed, open-access scholarly journal committed to advancing knowledge, innovation, and practical applications in the rapidly evolving field of Data Science. The journal serves as a global platform for researchers, academics, industry professionals, policymakers, and technology innovators to disseminate high-quality research that leverages data for scientific, industrial, social, and economic progress.

In today's data-driven world, organizations generate and process unprecedented volumes of information. Transforming this data into actionable intelligence requires advanced analytical methods, computational techniques, and responsible data practices. JDS publishes impactful research that contributes to the development of 

The journal welcomes interdisciplinary contributions that bridge statistics, computer science, artificial intelligence, machine learning, business analytics, engineering, healthcare, environmental sciences, and other data-intensive domains. By promoting scientific rigor, technological innovation, and ethical data usage, JDS aims to foster the advancement of data-driven solutions for real-world challenges.

All published articles are freely accessible under the Creative Commons Attribution (CC BY 4.0) License, ensuring global dissemination and unrestricted access to scientific knowledge.

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Topics 23
Data science research Big data analytics Applied data science Data lifecycle Data-driven insights Machine learning models Deep learning techniques Predictive analytics AI in data science Neural networks Statistical modeling Bayesian analysis Regression techniques Time series forecasting Multivariate statistics Data pipelines ETL processes Cloud data platforms Scalable data systems Real-time data processing Data visualization tools Interactive dashboards Visual analytics
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