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Call For Papers

The ICSMLBDIT bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Big Data, Machine Learning, Information Technology, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Scalable machine learning algorithms
  • Big data challenges in scalability
  • Distributed machine learning techniques
  • Real-time big data processing frameworks
  • Machine learning for large datasets
  • Big data analytics for IT scalability
  • Cloud computing and machine learning integration
  • Scalable architectures for data processing
  • Machine learning for resource optimization
  • Big data in edge computing environments
  • Applications of big data in IoT
  • Machine learning for performance tuning
  • Big data storage solutions for scalability
  • Federated learning for big data applications
  • Scalable data pipelines for ML
  • Machine learning for network optimization
  • Big data visualization for scalability
  • Machine learning for operational analytics
  • Big data governance in scalable systems
  • Future trends in scalable machine learning

Evaluation

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Submit Your Paper Now Confirm Your Participation Today
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