Registration summary
ConferenceICAML
ModeVirtual
ParticipationListener
Registration fee$135.00
Bank charges (5.8%)$7.83
Total payable$142.83
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICAML conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Machine Learning Algorithms +
This track focuses on the latest developments in machine learning algorithms tailored for big data analytics. Researchers are encouraged to present novel approaches that enhance the efficiency and accuracy of predictive modeling.
02 Distributed Computing for Big Data Processing +
This session explores the role of distributed computing frameworks, such as Hadoop and Spark, in managing and processing large-scale datasets. Contributions should highlight innovative techniques that optimize resource utilization and performance.
03 Real-Time Analytics and Decision Making +
This track addresses the challenges and solutions in real-time data analytics for immediate decision-making processes. Papers should discuss methodologies that enable timely insights from streaming data.
04 Deep Learning Techniques for Big Data +
This session invites research on the application of deep learning models to large-scale data sets. Submissions should focus on architectural innovations and their impact on data-driven insights and predictions.
05 Cloud-Based Analytics Solutions +
This track examines the integration of cloud computing with big data analytics to provide scalable and flexible solutions. Researchers are encouraged to present case studies and frameworks that leverage cloud resources for enhanced data processing.
06 Anomaly Detection in Large Datasets +
This session focuses on methodologies for detecting anomalies within vast data environments. Contributions should detail novel algorithms and their applications in various domains, including finance, healthcare, and cybersecurity.
07 Feature Engineering for Enhanced Model Performance +
This track emphasizes the importance of feature engineering in improving machine learning model outcomes. Papers should present innovative techniques for feature selection, extraction, and transformation in the context of big data.
08 Scalable AI Solutions for Industry Applications +
This session explores the deployment of scalable AI solutions across various industries leveraging big data. Researchers are invited to share insights on practical implementations and the impact of AI on operational efficiency.
09 High-Performance Computing in Data Science +
This track investigates the utilization of high-performance computing resources to accelerate data science workflows. Contributions should focus on benchmarking and optimizing algorithms for performance improvements.
10 Ethics and Governance in AI and Big Data +
This session addresses the ethical considerations and governance frameworks surrounding the use of AI and big data analytics. Papers should explore the implications of data privacy, bias, and accountability in AI systems.
11 Innovative Applications of AI in Engineering +
This track highlights the transformative role of AI technologies in engineering disciplines. Researchers are encouraged to present case studies that demonstrate the application of AI in solving complex engineering problems.
