Welcome👋, in this project focused on Predicting Apartment Sale Prices in Buenos Aires! Our endeavor aims to develop predictive models for estimating apartment sale prices in the bustling city of Buenos Aires based on a data from kaggle argentina-house-sale. With a commitment to rigorous analysis and methodical modeling, we seek to provide accurate forecasts that contribute to informed decision-making within the real estate market of this dynamic city. Join us as we delve into the complexities of real estate data and strive to offer valuable insights for strategic planning and investment.🚀

• Create a linear regression model🔍📈🔧

• Build a data pipeline for imputing missing values and encoding categorical features🛠️���🔌

• Improve model performance by reducing overfitting📈🔧🔍

• Create a dynamic dashboard for interacting with our completed model📊🖥️🔧

• Distribution of Prices based on latitude and longitude

• latitude, longitude and surface correlation

• Model pipeline structure

• Deploy the model in widget

  predict the price based on Size,Location and Neighborhood

• Click here to access to the open source data from kaggle

• Click here to access to the code source of the project