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most often when we are training neural networks to do classification we use the negative log likelihood but in practice if you actually go and call the function in pytoramp;#39;s or tensorflow that loss function will be called the cross entropy loss and so in this video I just quickly want to show you that training with negative log likelihood is actually the same as what they call cross entropy loss in pi torch or tensorflow so as our example Iamp;#39;m just going to draw the little Vector diagram for a small neural network so letamp;#39;s say weamp;#39;ve got the input X and X feeds into a number of layers hidden layers and what we then have is weamp;#39;ve got our little penultimate layer here which I will just calls it okay so after passing this through these hidden layers we end up with a little Vector Z here and let me just say that Z has like three dimensions and the values here can be between minus infinity and infinity and then what I do is I push Z through a function whi