This model will be Predicting Sales prices of the given house based on given features.
I completed a project to predict housing prices using machine learning techniques. The project involved cleaning and preprocessing a dataset of housing features, such as square footage, number of bedrooms and bathrooms, and location. I then explored the data using descriptive statistics and data visualizations to identify any patterns or correlations.
Afterward, I implemented a linear regression model using the Scikit-learn library to predict housing prices based on the features in the dataset. I evaluated the performance of the model using various metrics, including mean squared error and R-squared. Finally, I deployed the model to a web application using Flask, allowing users to enter housing features and receive a predicted price.
This project helped me develop skills in data cleaning, exploratory data analysis, machine learning, and web development. It also allowed me to gain experience in project management, as I had to plan and execute the project from start to finish.
If you want to see my source code, you can visit https://github.com/Lohitaditya/Linear-Regression-Model/tree/main