Machine-Learning-using-Python

Produced an in-depth report and built 10 machine learning models using 3 different datasets for unsupervised learning, regression and classification tasks. Performed Data Cleaning , feature selection and EDA to answer research questions which was contrasted against existing literature. PCA was done and K Means algorithm was performed to find homogenous groups of consumers of a wholesaler. Five different regression models were modelled to predict house prices in Boston and the best model was found. Four different classification models were created to classify diabetic patients and the best model was found.