Introduction to Machine Learning for Humanists and Social Scientists (Part 2 of 2)

Artificial intelligence/machine learning is transforming our world and opening new horizons for research. This 2-part workshop offers an introduction to neural networks, the core technology underlying modern AI, without assuming calculus/linear algebra or prior experience with coding. The emphasis will be on understanding the fundamentals of how a neural network learns to perform various tasks. All are welcome to attend including those outside of the humanities and social sciences.

Meet the Facilitator

Sarah-Jane Leslie, Professor of Philosophy and the Center for Statistics and Machine Learning, and Co-Director of Natural and Artificial Minds

After the Workshop

Continue your study of machine learning by attending the following workshops:

A Hands-On Introduction to Machine Learning (Parts 1, 2, 3 & 4) by Julian Gold and Gage DeZoort on January 15, 16, 17, 21
Getting Started with Large Language Models (Parts 1 & 2) by  Simon Park and Abhishek Panigrahi on January 22
Graph Neural Networks for Your Research by Gage DeZoort on January 22
Machine Learning for the Physical Sciences by multiple presenters on January 22

Sponsorship

This workshop is co-sponsored by Natural and Artificial Minds, the Center for Statistics and Machine Learning, and the Princeton Institute for Computational Science and Engineering.

To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.

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Co-hosted with: Research Computing

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