House Prices Prediction with Regression Modelling and Features Selection
Table of Contents Introduction Data Wrangling Model Introduction Language used: Python Goal: Prediction of house prices. Data used: Dataset from Properati website (https://www.properati.com.ar/). Two datasets: one for training (dataframe: dfef) and one for testing (dataframe: dfp) Link to the Dataset: https://www.kaggle.com/datasets/jluza92/argentina-properati-listings-dataset-20202021/data (1gb) Libraries used Library Description pandas Data manipulation and analysis to work with structured data numpy For numerical operations to work on large and multi-dimensional arrays and matrices sklearn used for machine learning algorithms for classification, regression, clustering, dimensionality reduction matplotlib....