• Want to understand trends or patterns?
• Want to pick-up some Machine Learning?
• Want to better interpret your data?
   

The Postdoctoral Association of Colorado, Boulder has organized this series of monthly tutorials/workshops on topics that may be useful to postdocs, students, and faculties across different disciplines. This month's tutorial, hosted on Zoom, is going to be on some Data Science techniques. Please join us on Zoom via the link:

https://cuboulder.zoom.us/j/287296657

Meeting ID: 287 296 657
Find your local number: https://cuboulder.zoom.us/u/abUqK3Stk

"Data science" is a catch-all term for a wide variety of workflows and analysis techniques, typically with the goal of discovering something about your data that someone can take action on. In this tutorial, we will use a few datasets as case studies to explore different aspects of data science:

- The "iris" dataset - load a "nice" dataset, then apply classification techniques to distinguish different types of flowers;

- A wine quality dataset - apply approaches to handling "high-dimensional" data to pick out which features of wine best distinguish their quality;
- A collection of recent papers from the bioRxiv related to coronaviruses - discover the joy and despair of data cleaning.

This tutorial will be done in Python. If you'd like to follow along, you'll need to have Python set up with the numpy, pandas, matplotlib, and sklearn packages installed, as well as Jupyter notebooks. Links to the datasets and helper scripts will be uploaded on this dedicated Github repository in advance for download.