Two ways of optimize the same function? I'm actually reading this tutorial about deepLearning and in particular about Logistic Regression.

I don't get why it first says to optimize logistic regression taking the max Probability and after using the Log loss function ?

Sorry you can explain me the point where him will use the Argmax and where Will use the Loss ?

you would not need only 1 of this 2 ?
The argmax is to get the class label prediction y_pred given a sample x. 

# symbolic description of how to compute prediction as class whose 
 # probability is maximal
 self.y_pred = T.argmax(self.p_y_given_x, axis=1)

The Loss function is used as optimization objective function to solve the coefficients W and b based on training data. On the tutorial, the loss function is the reverse the likelihood.