Mr. Senthil Bogana

Data First: Crafting Datasets for Effective ML Models

Abstract:

Machine Learning (ML) models are rapidly transforming industries—from healthcare and finance to transportation and cybersecurity. As their adoption accelerates, ensuring these models are accurate, reliable, and capable of generalizing to real-world scenarios becomes paramount. One of the most critical determinants of model success lies in the training process—particularly the quality, relevance, and diversity of the underlying data. In this session, I will share insights on the pivotal role data plays in shaping ML performance, emphasizing the need for strategic dataset selection, meticulous preprocessing, and rigorous validation practices. These elements are essential for building scalable, high-impact ML systems that deliver consistent and trustworthy outcomes across dynamic environments.