30 APR

28 MAY

2025

Neural Networks with Pytorch

This workshop series introduces participants to PyTorch and its applications in deep learning over 5 weeks.

University of York
30 Apr 2025 1:30 p.m. — 4 p.m.
7 May 2025 1:30 p.m. — 4 p.m.
14 May 2025 1:30 p.m. — 4 p.m.
21 May 2025 1:30 p.m. — 4 p.m.
28 May 2025 1:30 p.m. — 4 p.m.

This event is only for N8 researchers. Please use your University emails to sign up to ensure eligibility for this event.

Due to high volumes, this event is by application so signing up is not a confirmation of your place. You will be notified if you are sucessful at gaining a place on this course.

Date: April 30th, May 7th, May 14th, May 21st May 28th

Location: University of York

Cost: Free

Please note, by signing up to this workshop you are agreeing to attend all 5 dates. If you are unavailable for one date, you must discuss this with the programme trainer.

This workshop series introduces participants to PyTorch and its applications in deep learning. Designed for researchers and students interested in machine learning, the sessions provide hands-on experience with neural networks, from basic tensor operations to training custom models on real-world data.

Audience and Pre-requisites

With hands-on coding exercises and practical demos, this workshop is perfect for early career researchers looking to apply neural networks in their research or deepen their understanding of neural networks and their applications. PhD students and Post-Docs are welcome to take part.

You do not need any experience in machine learning to attend, but Basic Python Programming and Basic Linear Algebra knowledge is required.

You must bring your own laptop.

Agenda

A detailed agenda with session topics will be shared to registered participants.

What's included

This event is completely free to attend and refreshments will be included. Attendees are expected to arrange their own travel and accommodation. Bursaries are available to sucessful applicants who suffer financial, caregiving, or disability-related barriers to attendance.

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