Tutorial seminars presented as part of the Brookhaven National Laboratory AI/ML Working Group
Important
This is a snapshot of the original repository at matthewcarbone/AIML-tutorials, which was moved on 10 April 2024 to the AIML Working Group org. Please see the AIML Working Group Organization for the maintained version of this respository!
| Tutorial | Author | Colab link(s) | Presentation |
|---|---|---|---|
| NumPy and tabular data | Matthew R. Carbone |  |
link |
| K-nearest neighbors regression | Jackson Lee | |
link |
| Random forests | Matthew R. Carbone | |
link |
| Dimensionality reduction | Matthew R. Carbone | |
link |
| Gaussian processes | Maxim Ziatdinov | |
Coming soon! |
The event link on indico.bnl.gov can be found here.
| Tutorial | Author | Colab link | Presentation |
|---|---|---|---|
| General introduction to Python | Dakota Blair | |
link |
| Numpy and tabular data | Matthew R. Carbone | |
link |
| Introduction to machine learning | Yi Huang | |
link |
| Introduction to PyTorch and autograd | Yihui (Ray) Ren | |
link |
| Introduction of CNNs and image classification | Sandeep Mittal | |
link |
This work is partly supported by the Brookhaven National Laboratory Center for Computing Sciences Education and Support (CCSES), and by Brookhaven National Laboratory under Contract No. DE-SC0012704.
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