Please can anyone explain me the relation between maximum likelihood and how it is able to affect the optimal theta??
How is optimal theta related to maximum likelihood in logistic regression?
Hello @Shubhankit-Tiwari-1738649599558824,
Maximum Likelihood estimation is maximizing the likelihood P(Y|X).
As maximizing x is same as maximizing log(x), we maximize log(P(y|x)).
Now, comes the part where the theta is involved.
We assume that our model predicts the probability P(y|x), thats why that link function sigmoid. 
Therefore,
P(y|x) = sigmoid(theta[0] * x + theta[1])
Now when we maximize this, you can see the only variable is theta, and we optimize it so as to maximizing our likelihood.
The optimized theta is what you call optimized theta.
Happy learning 
Thanks
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