The Machine Learning Laboratory provides practical exposure to core machine learning concepts and algorithms used for data analysis, classification, prediction, and decision-making. The experiments cover supervised, unsupervised, and concept learning techniques, including neural networks, regression, clustering, probabilistic models, and decision trees. This laboratory helps students understand the practical implementation of machine learning algorithms and their applications in real-world problem-solving.