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Binary Crossentropy in its core!
It is a loss function that is widely used in Deep Learning, but the sad part is everyone just tells the name of the function & maybe the situation in which it can be used, no one tells what is this function when it should be used in reality, & how does it work internally? This blog aims to explain everything about Binary CrossEntropy in complete depth covering every formula & concept used in it.
5 min readOct 4, 2020
Binary Crossentropy is the loss function used when there is a classification problem between 2 categories only.
It is self-explanatory from the name Binary, It means 2 quantities, which is why it is constructed in a way that fits the problem of classification of 2 quantities.
Before starting the internal working of this loss/cost/error function, I would suggest you please read the blog of the significance of mean squared error written by me(link just below this paragraph), it helps you to make your base more fundamental for the working of this function.
