Course 2, Week 1 input normalization formula in slide 28 incorrect

The formula for normalizing the input training data to mu=0 and variance=1 (slide 28) is given as xnorm = (x - mu) / sigma^2, but this is incorrect. The 0-mean input should be divided by the sqrt(sigma^2).

In other words the correct formula for normalized inputs should be:

X_{norm} = (X - \mu) / \sigma

My own experiments in numpy seem to confirm, but would appreciate if someone can confirm.

Apologies, should be Week 1.

Hello @Marco_Morais,

Nice catch! If we check out the video version of the slide, we will see that the formula has been corrected there:

Note that it was announced that the slides are not maintained :slight_smile: