## Binary Log Regression
In this problem you will implement logistic regression in a two class setting.
Start by look at file [binary_log_regression.py](./binary_log_regression.py).
You will have to implement `BinaryLogReg` class along with all of it's functions.
We advise you to start with the constructor (`__init__`) and then move to any of the
`mu`, `loss`, `gradient_J_weight`, `gradient_J_bias`, `predict`.
Once you are finished implementing these functions you should implement `misclassification_error` and `step`.
Finally, once all other functions are implemented you should write `train` function.

Note that all functions but `train` are unit tested, so that you can verify your implementation.

To run the problem do: `python homeworks/log_regression/binary_log_regression.py` from the root directory of provided zip file, and then save and add the plots to your written submission.
