This repository is focused on different projects related to machine learning.
Project 1:
Name - House Price Prediction Model
Detail - We have been provided with a house price dataset containing various features and price of a house, and we need to build a model that can predict prices for new houses on the basis of their features. To know more about the dataset, see 'data_description.txt'.
Type - Supervised Learning, Regression Problem
Steps performed - Data Collection and Preprocessing, Exploratory Data Analysis(EDA), Feature Engineering, Model Selection and Training, Prediction
Models used - Linear regression, Ridge regression, Lasso regression, Support Vector regressor, Decision Tree regressor, XGB regressor
Results - Out of all these regression models, Decision Tree and XGB regressor performed the best with R2 score of 0.862 and 0.877 respectively.