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Exploratory data analysis and supervised learning analysis on the Ames Housing Prices dataset.

Home Page: https://www.albertobas.com/blog/ames-housing-prices-eda

License: Apache License 2.0

Jupyter Notebook 99.78% Python 0.22%
regression lasso data-preprocessing elastic-net random-forest-regressor bivariate-analysis ridge support-vector-regressor kernel-ridge univariate-analysis

ames-housing-prices's Introduction

Ames Housing Prices

Apache 2.0 licensed

About

Exploratory data analysis and supervised learning analysis on the Ames Housing Prices dataset in Jupyter notebook format.

For each analysis there is an English and a Spanish version.

Requirements

  • python==3.9.18
  • jupyter==1.0.0
  • numpy==1.26.0
  • pandas==2.1.1
  • matplotlib==3.8.0
  • seaborn==0.12.2
  • scipy==1.11.3
  • dask==2023.6.0
  • lightgbm==3.2.1
  • ipython==8.15.0
  • scikit-learn==1.3.0
  • xgboost==1.7.3

Running locally

$ git clone https://github.com/albertobas/ames-housing-prices.git
$ cd ames-housing-prices
$ conda env create --file environment.yml
$ conda activate ames_housing_prices
$ jupyter notebook

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