why should we maximize this loss
LOgisitic regression -gradient descent
Hey Abhishek,
We are not maximizing the loss.
Instead, we are maximizing the Log Likelihood Estimation. which is
sum[yi*log(h_theta_x) + (1-yi)*log(1-h_theta_x)]
Since we are maximizing this quantity, so let’s take negative of this, and we call it Cost Function.
now we want to minimize the cost function…
I hope clears your doubt
Thanks 
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