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This lecture introduces the concept of supervised learning efficiency, focusing on the Maximum Likelihood Estimation (MaxL) and unbiased estimators. Topics covered include asymptotically unbiased estimators, large sample properties, and the calculation of Mean Square Error (MSE). The instructor explains the importance of unbiased estimators in large datasets and their role in achieving accurate predictions.