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General Information

This is a pilot workshop, testing out a lesson that is still under development. The lesson authors would appreciate any feedback you can give them about the lesson content and suggestions for how it could be further improved.

High-dimensional datasets, or tabular data with many features describing each observation of a dataset, are increasingly commonplace in many research domains. How can researchers find patterns and extract insights from such complex and information-rich data? In this workshop, we will explore several tried and true methods that can help data analysts better understand their high dimensional data including: principal component analysis, data visualization, and regularized multivariate regression. As a result of participating in this workshop learners should be able to…

• Define, identify, and give examples of high dimensional datasets
• Visualize and explore high-dimensional data to reveal a research story
• Use dimensionality reduction techniques such as PCA to yield useful abstractions/summaries of complex, high dimensional data
• Understand the challenges associated with fitting both predictive (e.g., overfitting) and explanatory (e.g., avoiding multicolinearity) regression models to high-dimensional datasets
• Optimize high-dimensional multivariate regression models for either predictive or explanatory purposes via a combination of techniques including: PCA, feature selection, and regularization techniques (lasso, ridge, and elastic net)

Where: Data Science Institute, Room 1109, 447 Lorch Ct, Madison, WI 53706. Get directions with OpenStreetMap or Google Maps.

When: August 14-16, 2023. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Prerequisites: Learners are expected to have the follow prerequisite knowledge:

• Introductory Python programming skills (variable assignments, how to create a function, for loops, etc.) and familiarity with the Pandas package. If you need a refresher on Python before taking this workshop, please review the lesson materials from this Introductory Python Carpentries workshop.
• Some familiarity with basic machine learning concepts including train/test splits and overfitting is recommended, but not strictly required. For a refresher on machine learning basics, please review the lesson materials from the Intro to Machine Learning with Sklearn workshop

Accessibility: We are committed to making this workshop accessible to everybody. For workshops at a physical location, the workshop organizers have checked that:

• The room is wheelchair / scooter accessible.
• Accessible restrooms are available.

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email facilitator@datascience.wisc.edu for more information.

Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.

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Code of Conduct

Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Report a Code of Conduct Incident

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Collaborative Notes

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.

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Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey

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Schedule

This workshop is teaching a lesson in The Carpentries Incubator. Please check the lesson homepage for a list of lesson sections and estimated timings.

The lesson taught in this workshop is being piloted and a precise schedule is yet to be established. The workshop will include regular breaks. Please contact the workshop organisers if you would like more information about the planned schedule.

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Setup

To participate in a workshop, you will need access to software as described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

Please check the “Setup” page of the lesson site for instructions to follow to obtain the software and data you will need to follow the lesson.