ML Bubble 2026 – Machine Learning Awareness & Skill Building Challenge

Machine Learning is becoming an essential skill for engineers and is now a key component of major hackathons and industry projects. ML Bubble provides students with an opportunity to explore real-world problems and develop ML-based solutions according to their academic level. The event is divided into three tracks: FE – Explore & Identify Identify a real-world problem. Explain why Machine Learning can help solve it. Submit a short presentation or write-up. SE – Design & Solve Design an ML-based solution. Train a working model. Present results and evaluation metrics. Submit PPT and model. TE-BE – Design & Solve (Advanced) Build and train a working ML model. Present results and performance metrics. Include comparative analysis and deployment considerations. Submit PPT and model. Suggested Problem Domains Participants may choose problem statements from, but are not limited to, the following domains: Healthcare & Medical Technology Agriculture & Smart Farming Defense & National Security Cybersecurity Finance & FinTech Education Technology (EdTech) Smart Cities & Urban Development Environment & Sustainability Industrial Automation & Manufacturing Transportation & Logistics E-Commerce & Retail Analytics Human Resources & Recruitment Social Impact & Public Welfare Energy & Power Management Sports Analytics Media & Entertainment Natural Language Processing (NLP) Computer Vision & Image Processing Internet of Things (IoT) & Smart Systems Predictive Analytics & Decision Support Systems Note Participants are free to choose any domain, provided that the proposed solution involves a significant Machine Learning component and demonstrates its practical application to solve a real-world problem.