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Bias(편향) : Gap between the real problem and our model / The expected error created by using a model to apporoximate a real world function/relationship. 모델을 통해 얻은 예측값과 실제 정답과의 차이의 평균 f hat(x) : predicted value f(x) : true value Bias[^f(x)]=E[^f(x)−f(x)] Variance(분산) : change for different training data sets / The amount our predicted values would change if we had a differenct training dataset. It..

Key terms Y = f(x1, x2, x3) - want to improve sales (Y) of a product -> Y: output variable, dependent variable -control adveritsing budgets : sns(x1), streaming(x2), flier(x3) ->x1, x2, x3 : input variables, independent variables, predictors Key questions 1) What is the relationship between x1, x2, x3 and Y? -> learning 2) How accurately can we predict Y from x1, x2, x3? -> prediction data -- (l..