Data Science Training Workshop: Using Jupyter Notebook and R
Authors:
Leslie D. McIntosh, PhD, MPH
Kanstantsyia (Connie) Zabarovskaya, MBA, MITM
Lorinette S. Wirth, MPH
Attributions
We would like to thank developers of the following products for the opportunity to use their great tools:
- Hadley Wickham - dplyr package for R
- Max Kuhn, Steve Weston, Nathan Coulter, Mark Culp - C50 package for R
- Jupyter Project - Jupyter Notebook
Repo Contents
This repository contains Jupyter notebook files and data required for the workshop, and PDF version of the slides used in the workshop provided to the St. Louis Machine Learning and Data Science Meetup group on Tuesday, April 11, 2017. Notebook files will become available on the day of the workshop, the PDF of presentation, will be uploaded within a few days after that. If you have any questions please submit an issue to this repo.
The Jupyter notebook files can be run on Jupyter Notebook application, with the requirement of data files being available in the same directory with the notebooks, however you must have all the necessary R packages installed. To run the notebooks, download the notebooks folder with all the included files, and run any of the .ipynb files inside Jupyter.
Workshop Prerequisites (if you want to follow hands-on portion)
While getting ready for the workshop is optional, it will allow you to follow the instructors during the workshop and perform the hands-on exercises. Come at least 15 min early if you have issues with installing the tools, so we have time to try and help you.
Please follow the installation_instructions.md file in this repo to download and install tools, as well as the data for the workshop. if you have any problems or issues with the installation please let us know by submitting an issue in this repo.