In This video, we will discuss a couple of important terminologies related to machine learning, bias: Bias in Machine Learning is defined as the phenomena of observing results that are systematically prejudiced due to faulty assumptions. variance : Variance, in the context of Machine Learning, is a type of error that occurs due to a model's sensitivity to small fluctuations in the training set. High variance would cause an algorithm to model the noise in the training set. This is most commonly referred to
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