A Hands-On Introduction to Machine Learning (Part 2 of 4)

This mini-course provides a comprehensive introduction to machine learning. Part 1 introduces the machine learning process and shows participants how to train simple models. Part 2 covers model evaluation and refinement. Artificial neural networks are introduced in Part 3. A survey of different neural network architectures is presented in Part 4. The mini-course concludes with three specialized choices for Part 5:

- Machine Learning for the Physical Sciences on January 22 at 2 PM
- Getting Started with Large Language Models on January 22 & 23 at 2 PM
- Graph Neural Networks for Your Research on January 22 at 2 PM

Attendees should have some familiarity with Python and basic calculus.

Presenters

Julian Gold, DataX Data Scientist, Center for Statistics and Machine Learning
Gage DeZoort, Lecturer and Postdoctoral Research Associate, Physics

Preparation

If you are new to machine learning then consider attending the this workshop as preparation:

Introduction to Machine Learning for Humanists and Social Scientists (Parts 1 & 2) by Prof. Sarah-Jane Leslie on January 13 and 14

Sponsorship

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

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

Contact the organizers