I'd say I have some understanding of backpropagation, however I am not really sure of the total loss being calculated. Let us take the example below : After 1 forward pass when I have to update the parameters, I basically have to find answers to the question - What is the change in loss with respect to the change in a certain parameter i.e. if I were to update parameter w5 then, I need to calculate $$ \frac{\partial L}{\partial w_5} = \frac{\partial L}{\partial o_1} \cdot \frac{\partial o_1}{\partial w_5} $$ So how does the total loss that I calculated after a forward pass even matter? Is it simply for logging(keeping track of)? Another doubt that I have is: What exactly is this graph indicating? If it is the Loss value for different set of parameter values, then shouldn't it be a discrete function?

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