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welcome to our course loss function and in this part of our course we are going to have cross entropy loss or what we call the negative log likelihood so lets first have the basic concept about loss function what is a loss function it evaluates how a certain algorithm models the data so it means we would like here to model the real phenomenon what is really happening in the real world we would like our model to perform that reality so we have some evaluation methods to understand that these evaluation metrics may depend on what kind of model we are using or what kind of algorithm we are using for the model it could be regression and it could be classification so when the deviation is high we mean to say that the loss function is large 2. and our target here is that we would like to minimize the error in as much as possible so that means the deviation should be lesser and lesser and in some cases if not in most cases we would like to reduce the error in our prediction and thats why in