House-Price-Prediction

Ames Housing dataset with 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges to predict the final price of each home.

Approach:

1.Exploratory Data Analysis

  • EDA to get better understanding of dataset
  • Visualization of data
  • Understanding the nature of data
  • Relationship of features with target variable SalePrice

2.Data Cleaning and Data Preparation

  • Dealing with missing values
  • Dealing with outliers
  • Feature Engineering
  • Feature Transformation

3.Predictive Modeling

  • Ridge Regression
  • Lasso Regression
  • ElasticNet Regression

Detailed description of Dataset can be found here: https://www.kaggle.com/c/house-prices-advanced-regression-techniques