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A Kaggle competition in which to the target variable is the price of a property. Using various ML Regression algorithms and hyper parameter tuning, the model reaches 92.0% accuracy.

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Housing-Price-Regression

A Kaggle competition in which the target variable is the price of a property. Using various ML Regression algorithms and hyper parameter tuning, an optimal Gradient Boosting Model is created

Medium Link : https://medium.com/@p99bratislav/regression-models-on-kaggles-house-pricing-competition-309286702b09

Directory Layout

  • check_me_out : images of project results, analyses and model evalutions

  • house-prices-advanced-regression-techniques : train and test data supplied by Kaggle

  • wrangled_data : data ready for models to be generated. Created by cleaning, wrangling, imputing data supplied by Kaggle.

  • data_process.py : py script whichc preps data for models, output in wrangled_data/

  • regression_models.py : py script performing various ML Regression Models

  • sources.txt: compilation of links guiding me in my study

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A Kaggle competition in which to the target variable is the price of a property. Using various ML Regression algorithms and hyper parameter tuning, the model reaches 92.0% accuracy.

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