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

• https://emilyriederer.netlify.app/post/writing-a-tech-talk/

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