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This is the pipeline for the design of a Random Forest Regression model which predicts the final sale price of a residential home, implemented in PySpark.

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House Prices Regression Model in Spark

Language: PySpark (Databricks Archive file with .dbc extension)

Introduction: This project, part of a Kaggle competition, makes use of a dataset describing hundreds of residential homes which were put up for sale in Ames, Iowa, in the United States, between 2006 and 2010. The dataset contains 79 explanatory features in total. The aim of the project is to predict the final price of each home. The model makes use of a Random Forest Regression algorithm.

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This is the pipeline for the design of a Random Forest Regression model which predicts the final sale price of a residential home, implemented in PySpark.

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