Kaggle-House-Price-Prediction

I have created this repositry as part of my kaggle journey by playing around with a dataset and trying to build a proper flow of various tasks used in a typical machine learning algorithms

Dataset Used :

https://www.kaggle.com/c/home-data-for-ml-course/data

or can also find the dataset here https://github.com/vishalbansal-1650/Kaggle-House-Price-Prediction/tree/main/Data

Here are the steps which i have performed in this notebook

Exploratory Data Analysis

1. Univariate Analysis

2. Bivariate Analysis

3. Data Preprocesing steps

4. Feature Engineering

5. Model Building

   5.1 Train-test split
   5.2 Feature Scaling
   5.3 Ensemble Algorithms 
       A) Bagging
       B) AdaBoosting
       C) Random Forest
       D) Gradient Boosting
       E) XGBoost
       F) LightGBM
       G) CatBoost
   5.4 Blending

Test Prediction

https://github.com/vishalbansal-1650/Kaggle-House-Price-Prediction/blob/main/submission/submission.csv

Future Work:

A.) Will add weight optimization function for blending
B.) Use Feature Selection and train model on those selected features