Open JessicaS11 opened 2 months ago
Looked through some of the survey responses last week, and did a bit of thinking on what might make sense for an ICESat-2 Machine Learning tutorial. There's a range of interests (many research topics) and skill levels (from Masters/PhD students to Postdocs with years of experience), so a little tricky to gauge what an interesting topic and difficulty level would be. Doing a braindump of possible combinations for now:
Task:
Methods:
Hi Wei Ji! Thank you for your valuable comments and ideas. We will be having an ML tutorial on Tuesday, that will cover a decision tree method (probably SWE) and ANNs (probably snow depth). If you would like to further develop your ideas, please don't hesitate to contact us. We are reaching out to tutorial leads to discuss/refine the tutorial content.
Thanks Wei Ji. I would vote for the Using Pytorch with a framework like Lightning, Huggingface, etc
and try to make it easier by using AutoML and wrap all the math and calculations in a few lines, like calling transformers
library of hugging face. I can help if needed.
Thanks for chiming in! I was looking at https://github.com/uwhackweek/schedule-2024/issues/39 and didn't want there to be too much of an overlap in terms of tasks/methods. I've already scheduled a meeting with Jessica actually to discuss about what ICESat-2 topic would be suitable, but could set up another one with you @NCristea and @ZihengSun to maybe talk about what ML method to teach.
@weiji14 yeah sure, I would love to chat about it.
Also happy to expand our meeting invitation if that day/time works for all!
Great - I am usually available in the morning - would Monday 9am work?
Lead: Wei Ji Leong Date: 21/08/2024 Start Time: 0945 Duration: 45 Description:
Details
### Learning Outcomes * outcome1 * outcome2 * outcome3 ### People Developing the Tutorial (content creation, helpers, teachers) ### Summary Description ### Dependencies (things people should know in advance of the tutorial) ### Technical Needs (GPUs? Large file storage? Unique libraries?) - NVIDIA T4 GPU