The cross entropy loss function -log(\hat{y}) is *not* the inverse function of `sigmoid`

. I also don’t know what you mean by avoiding Euler’s constant here: note that `log`

means natural logarithm in Machine Learning, so e is involved.

Here is a thread from mentor Raymond that explains how the loss function works and why it is defined the way it is.

Here’s another thread that includes a graph of log(z) which will help with the intuition.