Workshop 05/26/2021

This is the second of our workshops devoted to linear algebra, which forms
the foundation of many algorithms in data science.
In part I of the series (maybe with a link to the video?)
we introduced vector and matrix algebra, and briefly looked
at the intriguing and ever so useful Singular Value Decomposition (SVD).
In this workshop, we will take a deeper into the SVD. We will explain how
it is derived, how it can be computed, and also how it is used.

Want to learn more about trends like AI, IoT and wearable tech? In one hour, we will cut through the hype by building a “smart” fitness tracker using your own mobile device. We’ll do hands-on exercises:
you’ll acquire data from sensors, design a step counter and train a human activity classifier. You will leave motivated and ready to use machine learning and sensors in your own projects!

In this workshop, Dora will illustrates how natural language processing (NLP) can be used to answer social science questions. The workshop will focus on applying NLP to analyze the content of 15 US history textbooks used in Texas, to analyze the representation of historically marginalized people and groups. The workshop is based on a paper (https://journals.sagepub.com/doi/pdf/10.1177/2332858420940312) that also has an associated toolkit, and it will provide examples of how this toolkit can be used using a Jupyter notebook that will be made available.

(ps Dora was recently in the HAI newsletter:
https://hai.stanford.edu/news/whose-history-ai-uncovers-who-gets-attention-high-school-textbooks)