Flex Conference (Physical / Digital)

International Conference on Advanced Machine Learning Models in Data Science (ICAMLDS - 26)

6th - 7th August 2026, Macau, China

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Call for Paper

The ICAMLDS provides a supportive platform for both experienced researchers and early-career academicians to present their work and gain recognition. The conference covers diverse topics such as Data Science encouraging participation from emerging researchers and fostering academic growth.

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

  • Advanced machine learning techniques
  • Deep learning models in data science
  • Ensemble methods for predictive analytics
  • Feature selection in machine learning
  • Model evaluation and validation techniques
  • Transfer learning applications in data
  • Unsupervised learning in big data
  • Reinforcement learning in practice
  • Machine learning for time series data
  • Ethics of machine learning applications
  • Explainable AI in data science
  • Big data challenges for machine learning
  • Applications of neural networks
  • Machine learning in finance analytics
  • Data preprocessing for machine learning
  • Scalable machine learning algorithms
  • Applications of AI in industry
  • Collaborative machine learning frameworks
  • Future directions in machine learning
  • Machine learning for social good

Review & Publication

Submissions will be reviewed to ensure quality and relevance, with a focus on encouraging emerging research contributions. Accepted papers will be presented and considered for publication opportunities.

Registration

Early-career researchers are encouraged to register and present their work, gaining valuable feedback and academic exposure.

Publication

The conference provides opportunities for emerging researchers to publish their work in recognized platforms.

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Important Dates

Early Bird Registration :7th July 2026

Paper Submission Deadline :12th July 2026

Last Date of Registration : 22nd July 2026

Date of Conference : 6th - 7th August 2026

Supporting Academic Continuity

APSTE ensures that research and publication processes continue without interruption in the current global situation. Participants can present their work through digital and integrated formats.

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