International Conference on Machine Learning, Computer Software and Applications (ICMLCSA) - PhD Coaching Classes International Conference on Machine Learning, Computer Software and Applications (ICMLCSA) - Ludhiana
International Conference on Machine Learning, Computer Software and Applications (ICMLCSA)

International Conference on Machine Learning, Computer Software and Applications (ICMLCSA)

Date 20 Feb, 2026
Venue Belgaum, Karnataka, India
Type Offline

Event Overview

The International Conference on Machine Learning, Computer Software and Applications (ICMLCSA) will be held on 20 February 2026 in Belgaum, Karnataka, India. The conference aims to bring together eminent academic scientists, researchers, and research scholars to exchange knowledge, share research findings, and discuss advancements across all areas of machine learning, computer software, and related applications. 

ICMLCSA serves as a premier interdisciplinary platform for researchers, practitioners, and educators to present and deliberate on recent innovations, emerging trends, key challenges, and practical solutions within these rapidly evolving fields. 

The event is organized by Research Conferences in Belgaum, Karnataka, India.

Key Information

Event Status

Active

Organizer

Research Conferences

Organizing Secretary

Conference Coordinator

Conference Inquiry Email-ID

info.researchconferences@gmail.com

Program Schedule

Physical Schedule

08:30 AM – 09:00 AM : On-Site Check-In & Welcome Coffee

09:10 AM – 09:30 AM : Inaugural Address & Conference Overview

12:00 PM – 01:00 PM : Networking Lunch

03:00 PM – 03:15 PM : Closing Ceremony & Awards

Virtual Schedule

09:00 AM – 09:10 AM : Virtual Check-In & Orientation

12:00 PM – 01:00 PM : Break

03:00 PM – 03:15 PM : Closing Ceremony & Digital Certificate Instructions

Organizer Information

Research Conferences (RC)

Email: info.researchconferences@gmail.com

Website: researchconferences.in

Major topics covered for this event

Machine Learning  

  • Supervised and Unsupervised Learning
  • Reinforcement Learning
  • Deep Learning and Neural Networks
  • Bayesian Methods and Probabilistic Models
  • Graph Neural Networks and Network Analysis
  • Explainability and Interpretability in AI
  • Fairness, Accountability, and Ethics in ML
  • Optimization in Machine Learning
  • ML in Healthcare, Finance, and Other Industries
  • Transfer Learning and Domain Adaptation
  • Natural Language Processing and Vision-based Applications
  • Federated Learning and Distributed Systems
  • Applications in Robotics and Autonomous Systems

  

Computer Software and Applications

  • Software Development Methodologies
  • Cloud Computing and Distributed Systems
  • Cybersecurity in Software Systems
  • Software Engineering for AI and ML Applications
  • Embedded Systems and IoT Software
  • Human-Centric Computing and Interfaces
  • Software Testing, Validation, and Verification
  • Agile and DevOps Practices
  • Programming Languages and Compilers
  • Systems for Edge and Fog Computing
  • Big Data Processing and Analytics Platforms
  • Green and Sustainable Software Engineering
  • Software Systems in Healthcare and Education

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