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 # Linear-Regression-Model-for-House-Price-Prediction
-Linear Regression Model for Real State House Price Prediction
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+In this tutorial you will learn how to create Machine Learning Linear Regression Model. You will be analyzing a house price predication dataset for finding out price of house on different parameters. You will do Exploratory Data Analysis, split the training and testing data, Model Evaluation and Predictions. 
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+Problem Statement - A real state agents want the help to predict the house price for regions in the USA. He gave you the dataset to work on and you decided to use Linear Regressioon Model. Create a model which will help him to estimate of what the house would sell for.
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+Dataset contains 7 columns and 5000 rows with CSV extension. The data contains the following columns :
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+'Avg. Area Income': Avg. Income of householder of the city house is located in.
+'Avg. Area House Age': Avg. Age of Houses in same city.
+'Avg. Area Number of Rooms': Avg. Number of Rooms for Houses in same city.
+'Avg. Area Number of Bedrooms': Avg. Number of Bedrooms for Houses in same city.
+'Area Population': Population of city.
+'Price': Price that the house sold at.
+'Address': Address of the houses.