A journey starting from the standard formulation of linear regression, moving on to the probabilistic approach, and then progressing to Bayesian linear regression.
Read it!Dilated, transposed, and separable convolutions explained with informative animations.
Read it!To avoid responding with "that's what Andrew NG said" when asked about the reason behind choosing an 80% training and 20% validation split, consider this explanation.
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