Introduction to Machine Learning (Part 3 of 5)

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 a hackathon during Part 5 where participants will work on a small, end-to-end machine learning project chosen from one of multiple domains (e.g., computer vision, natural language processing).

Meet the Facilitator: Gage is a postdoctoral researcher in the Physics department.

What to Expect: Multi Session

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: PICSciE/Research Computing

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