Notes by Lex Toumbourou

An operation between 2 vectors that returns a number.

A loss function for binary and multi-label classification, also known as log loss.

Resize images to a larger intermediate size before augmenting.

A loss function for multiclass classification: softmax followed by negative log-likelihood.

A measure of how well one probability distribution encodes events from another.

A measure of uncertainty — highest when all outcomes are equally likely, lowest when one dominates.

a multi-class classification loss function

Converts a vector of numbers into probabilities that sum to 1.

Squeezes any number into a range between 0 and 1.

When production data diverges significantly from the training dataset