House Price Predictions Using Keras

This is a starter tutorial on modeling using Keras which includes hyper-parameter tuning along with callbacks. Creating a Keras-Regression model that can accurately analyse features of a given house and predict the price accordingly. We would be using numpy and pandas for processing our dataset, matplotlib and seaborn for data visualization, and Keras for implementing our neural network. Also, we would be using Sklearn for outlier detection and scaling our dataset. We would first see all the features having missing values. This would include data from both training and testing data.