International Conference on Big Data Analytics and Machine Learning Frameworks (ICBDAMLF - 27)

This track focuses on the latest methodologies and technologies in big data analytics. Researchers are invited to present innovative approaches that enhance data processing and interpretation.

This session explores various machine learning frameworks and their practical applications across different industries. Contributions that demonstrate the effectiveness of these frameworks in solving real-world problems are encouraged.

This track examines the role of cloud computing in facilitating big data analytics. Papers should address scalability, performance, and security challenges associated with cloud-based data processing.

This session delves into artificial intelligence algorithms specifically designed for predictive analytics. Submissions should highlight novel techniques that improve prediction accuracy and efficiency.

This track focuses on innovative data integration techniques that enhance the interoperability of IT systems. Researchers are encouraged to present solutions that address data silos and improve data accessibility.

This session addresses the challenges of scalable computing in the context of big data. Contributions should explore architectures and algorithms that enable efficient processing of large datasets.