Solhemi/Land_auction_price_prediction_model_in_Addis

This repo contains files and code compiled in an attempt to build a machine learning model for predicting the auction prices per square meters of land in the African capital, Addis Ababa. # Land_auction_price_prediction_model_in_Addis This repo contains files and code compiled in an attempt to build a machine learning model for predicting the auction prices per square meters of land in the African capital, Addis Ababa. Historic data from seven(7) consecutive bid results have been extracted, cleaned and wrangled to lay the foundations for building a regression model to predict future prices for upcoming land auction bids. The entire project follows these steps to uncover insights and build a model:- 1. Collect and clean data. 2. Derive core insights using Exploratory Data Analysis. 3. Visualize findings of Exploratory Data Analysis using built-in Python visualization libraries and Power BI. 4. Choose a suitable Machine Learning model like (Regression, XGBoost) and train data. 5. Test and fine tune model for minimized margins of error. 6. Deploy, test and monitor land auction price prediction model in real-time.