(ICMLMA - 26) | Hybrid Event
20th - 21st October 2026 | Zurich, Switzerland

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International Conference on Machine Learning Models and Applications
(ICMLMA - 26)

20th - 21st October 2026 Zurich, Switzerland (Hybrid Event)

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Call for Paper

The ICMLMA is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Artificial Intelligence,Data Science,Machine Learning, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Advancements in machine learning algorithms
  • Applications of machine learning in healthcare
  • Machine learning for financial forecasting
  • Deep learning techniques for data analysis
  • Reinforcement learning in real-world scenarios
  • Transfer learning in machine learning models
  • Machine learning for image and video analysis
  • Ethics in machine learning applications
  • Machine learning for natural language processing
  • Scalability challenges in machine learning
  • Interpretable machine learning models
  • Machine learning in cybersecurity applications
  • Federated learning for decentralized data
  • Machine learning for environmental monitoring
  • Challenges in deploying machine learning models
  • Machine learning in personalized medicine
  • Automated machine learning techniques
  • Machine learning for social media analytics
  • Impact of quantum computing on machine learning
  • Future trends in machine learning research
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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