Gradient Descent Implementation

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This project implements a logistic regression classifier with gradient descent algorithm for machine learning, as a part of Introduction to Artificial Intelligence course at KAU. The goal is to train the model to classify provided data as "0" or "1" (doesn't have heart disease or has heart disease).

How to run using command line

A- Training:
1- python Heart-Disease-Classifier.py T1
        This commend will train linear model. it will output linear_thetas.npy file which is necessary for testing.
2- python Heart-Disease-Classifier.py T2
        This commend will train 2nd ord model. it will output linear_thetas.npy file which is necessary for testing.

B- Testing:
1- python Heart-Disease-Classifier.py V1
        This command will test the trained linear model. output will be shown in cmd line + Output_Linear.csv file
2- python Heart-Disease-Classifier.py V2
        This command will test the trained 2nd ord model. output will be shown in cmd line + Output_poly_ord2.csv
        file