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A machine learning project in R to understand the impact of various predictors like human population, CO2 emissions, Human population, and GDP on global temperatures

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IDENTIFICATION OF PREDICTORS FOR CLIMATE CHANGE EFFECTS

The final project notebook is named "WHOCaresReport.nb.html" and is available in this folder.

The datasets are located in the folder "Data sets".

Code written to preprocess the datasets and analyse the data is stored in "Scripts" folder.

Link to the screencast - https://www.youtube.com/watch?v=qQgJpYrw-WY

Link to the website - https://who-cares.gitlab.io/rblog/

Dependencies - To run this notebook, make sure you have installed the following R packages: magrittr, dplyr, ggplot2, corrplot, sqldf, tidyr, ggthemes, cowplot, Hmisc, psych, reshape2, readr, broom, ridge, caret, tseries, forecast, bootstrap

Notes:

  1. For some of the scripts to run, set the correct working directory
  2. All the pre processing scripts were run from the "Data sets" folder.
  3. The script "MergeAndAnamoly.R" is run under the folder "Data sets/PreProcessed"

Link to the notebook: https://gitlab.com/who-cares/data-science-with-r/blob/master/WHOCaresReport.nb.html

Please download the notebook to view it better.

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A machine learning project in R to understand the impact of various predictors like human population, CO2 emissions, Human population, and GDP on global temperatures

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