Machine Learning, Deep Learning, Algorithms, Loss Function, Optimization.
θused to define the data generating distribution. An estimator θˆm is said to be unbiased if bias(θˆm) = 0, which implies that E(θˆm) = θ. Variance and Standard Error The variance of an estimator Var(θˆ) where the random variable is the training set. Alternately, the square root of the variance is