California-Housing-Price-Prediction

• The Kaggle dataset on California Housing Price was used to perform the primary EDA and to build linear, ridge, lasso and elasticnet machine learning regression models.
• Various iterations were done like scaling and normalizing the data, tuning the model parameters using GridSearchCV to evaluate its effects on the models.
• An accuracy of 68% was achieved in predicting location specific housing prices in California state with Ridge Regression model.