Regression:
The simple Linear Regression and the Logistic Regression model have been implemented. The dataset used is BSOM, which is confidential, so cannot be shared public, but the code can be run for any dataset. The code have been implemented from scratch without use of any in-built methods. Cost optimization is done using Gradient Descent. For Linear Regression, Mean squared error and Rsquare metric has been used for evaluation. And for Logistic Regression, F1 score, Precision and Recall scores are used for evaluation.