Abstract

MLNova is a structured platform designed to bridge the gap between theoretical knowledge and practical application in machine learning. Focused on enhancing student learning, the platform offers a path for beginners to explore key concepts in data preprocessing and model evaluation. Through interactive modules, MLNova delivers prerecorded lessons and real-world projects, allowing learners to experience hands-on engagement. This paper outlines the platform’s design, methodology, and the impact of interactive learning on improving comprehension of machine learning principles. Early feedback indicates a significant improvement in user engagement and learning outcomes.