I have one small doubt, that how can we get to know we have reached to Minimum Value if J has not returned 0.

In other ways, when will we get to know that, this is the minimum value of J, using alpha(learning rate).

I have one small doubt, that how can we get to know we have reached to Minimum Value if J has not returned 0.

In other ways, when will we get to know that, this is the minimum value of J, using alpha(learning rate).

It might be a near impossibility to reach a cost of 0 because fundamentally the model makes predictions with propabilities.

You can not be sure that the model has reached a global optima either, you can hope so. Most of the times its a local optima but as long as its fulfiling the prediction demands with good accuracy could be good enough.

Typically you might use a plot of the cost value vs. the number of iterations, and observe whether the cost history is reaching a stable value.

Thanks for replying. I too got to know that if that values of w is not changing i.e. remains constant. then we get towards the required solution.

Please correct me if I am wrong.

Are w the weights refered to in this case?

No, w is the slope for the Regression Model

Its also refered as a weight!