Machine learning research lab group meetings
- Spring 2024
- Fall 2023
- Spring 2023
- Fall 2022
- Spring 2022
- Fall 2021
- Spring 2021
- Fall 2020
- Spring 2020
- Fall 2019
Advice on preparing talks/slides
Ideas for talks
- Don’t use VSCode
- https://github.com/mlabonne/llm-course
- https://github.com/microsoft/generative-ai-for-beginners
- https://github.com/microsoft/ML-For-Beginners
- When there are new people in lab at the beginning of a semester, tutorial about
- git
- data.table
- ggplot2
- Grad student reading group Programming for Data Science in R
- Z. Yang, Q. Xu, S. Bao, X. Cao, and Q. Huang. Learning with multiclass auc: Theory and algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
- https://developers.google.com/machine-learning/guides/rules-of-ml
- anything from the Murphy book, https://github.com/probml/pml-book/releases/latest/download/book1.pdf
- Causality for Machine Learning https://arxiv.org/abs/1911.10500
- Efficient and Modular Implicit Differentiation, https://arxiv.org/abs/2105.15183
- Hyperparameter optimization with approximate gradient, https://arxiv.org/pdf/1602.02355.pdf
- Deep Implicit Layers Tutorial at NeurIPS 2020, http://implicit-layers-tutorial.org/
- anything from the Sussex PAL reading group, https://wearepal.ai/reading
- Intro to jax in Python, https://jax.readthedocs.io/en/latest/notebooks/quickstart.html
- Tutorial how to use Tensor Processing Units (TPUs), https://cloud.google.com/tpu/docs/tpus
- Jenny Bryan on R debugging and minimal reproducible examples, https://www.youtube.com/watch?v=vgYS-F8opgE
- https://github.com/ReeceGoding/Frustration-One-Year-With-R
- Changepoint review paper https://arxiv.org/pdf/2012.12814.pdf
- https://github.com/matloff/TidyverseSkeptic/blob/master/READMEFull.md