This project aims at predicting median house values in Californian districts from a given number of features from these districts. This project perform exploratory analysis for finding patterns and correlation in data followed by cleaning and massaging data. Finally I build a machine learning pipeline to predict the prices. I use following regression techniques
- Linear Regression : Linear classifier
- Support Vector Classifier : Linear classifier
- RandomForest Regressor: Non-Linear Classifier