
VisualML is an interactive web application designed to simplify the learning of Machine Learning concepts. The platform integrates visual simulations, quizzes, and user performance tracking to enhance understanding and engagement. Users can explore different ML topics such as Regression, Classification, Clustering, and Neural Networks through intuitive interfaces and dynamic visualizations. The system also provides quizzes with instant feedback to evaluate user understanding. The project is deployed using Firebase, enabling real-time authentication and hosting. The combination of visualization and interactivity makes VisualML an effective tool for beginners in Machine Learning.
Machine Learning, Web Application, Gamification, Firebase, Education, Interactive Learning.
Machine Learning, Web Application, Gamification, Firebase, Education, Interactive Learning.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
