International Conference on Big Data-driven Machine Learning for IT Optimization

ICBDMLITO

23rd Jan – 24th Jan 2027 Istanbul, Turkey

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Registration Summary

Conference ICBDMLITO

Date 23rd Jan – 24th Jan 2027

Location Istanbul, Turkey

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

Calculated based on 5.8% of the registration fee

Discount USD 0.00

Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Big Data Analytics +

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

SDG 9 SDG 12

02 Machine Learning Techniques for IT Optimization +

This session will explore the application of machine learning algorithms in optimizing IT systems. Contributions should highlight novel techniques that improve performance and efficiency in IT operations.

SDG 8 SDG 9

03 Predictive Analytics in Engineering +

This track emphasizes the role of predictive analytics in engineering applications. Papers should discuss the integration of predictive models to enhance decision-making processes in various engineering domains.

SDG 4 SDG 9

04 Intelligent Systems and Automation +

This session will delve into the development of intelligent systems that leverage big data and machine learning for automation. Submissions should focus on case studies and frameworks that demonstrate successful implementations.

SDG 9 SDG 11

05 Cloud Computing for Scalable Data Solutions +

This track addresses the challenges and solutions related to cloud computing in the context of big data. Researchers are encouraged to present scalable architectures that facilitate efficient data storage and processing.

SDG 9 SDG 12

06 Data Governance and Ethics in AI +

This session will examine the principles of data governance and ethical considerations in AI applications. Contributions should address frameworks that ensure responsible use of data in machine learning.

SDG 16

07 Performance Analysis of Machine Learning Models +

This track focuses on the evaluation and performance analysis of various machine learning models. Papers should provide insights into metrics, benchmarks, and methodologies for assessing model effectiveness.

SDG 9 SDG 12

08 Integration of IT Infrastructure and Big Data +

This session will explore the integration of IT infrastructure with big data technologies. Researchers are invited to discuss strategies that enhance interoperability and system performance.

SDG 9 SDG 11

09 AI Algorithms for Enhanced Decision Making +

This track will focus on the development and application of AI algorithms that support decision-making processes. Submissions should highlight innovative algorithms that improve outcomes in IT optimization.

SDG 9 SDG 16

10 Analytics Frameworks for Real-Time Data Processing +

This session will examine frameworks designed for real-time data analytics. Contributions should discuss architectures that enable rapid data processing and actionable insights.

SDG 9 SDG 12

11 Innovations in IT Optimization Strategies +

This track will showcase innovative strategies and technologies for optimizing IT systems. Researchers are encouraged to present case studies and theoretical advancements that contribute to IT innovation.

SDG 9 SDG 12