Lec-38: Mean Squared Error (MSE) | Machine learning
Mean Squared Error (MSE) is a common metric used to evaluate the accuracy of a predictive model by measuring the average squared difference between the predicted and actual values.
In this video, we will discuss how MSE is calculated and its significance in model evaluation and optimization.
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Timestamps:
00:00 - What is Mean Square Error(MSE)?
03:25 - Example of Mean Square Error
05:46 - Difference b/w predicted and actual values
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