Skip to content
@machine-learning-tutorial

machine learning tutorial

Hi there 👋! My name is Andrea Santamaria Garcia and I am an accelerator physicist interested in machine learning applications to particle accelerators.

You can find here a series of tutorials (lectures + hands-on Python notebooks) that I have used in master level university lectures and specialized accelerator physics conferences and workshops.

The content is targeted to physicists that have little to no previous experience in machine learning.

Hope you find it useful!

Currently available machine learning tutorials

Citation of material required!

If you find any of the content useful and/or you re-use any of the content, please cite it accordingly:

Pinned Loading

  1. bayesian-optimization bayesian-optimization Public

    An introduction to Bayesian optimization with an example of accelerator tuning task.

    Jupyter Notebook

  2. neural-networks neural-networks Public

    Basic neural network tutorial notebooks

    Jupyter Notebook 2

  3. reinforcement-learning reinforcement-learning Public

    Jupyter Notebook

Repositories

Showing 4 of 4 repositories
  • .github Public
    machine-learning-tutorial/.github’s past year of commit activity
    0 0 0 0 Updated Jul 8, 2024
  • machine-learning-tutorial/reinforcement-learning’s past year of commit activity
    Jupyter Notebook 0 GPL-3.0 0 0 0 Updated Jul 8, 2024
  • bayesian-optimization Public

    An introduction to Bayesian optimization with an example of accelerator tuning task.

    machine-learning-tutorial/bayesian-optimization’s past year of commit activity
    Jupyter Notebook 0 GPL-3.0 0 0 0 Updated Jul 4, 2024
  • neural-networks Public

    Basic neural network tutorial notebooks

    machine-learning-tutorial/neural-networks’s past year of commit activity
    Jupyter Notebook 2 GPL-3.0 0 0 0 Updated Jul 4, 2024

People

This organization has no public members. You must be a member to see who’s a part of this organization.

Top languages

Loading…

Most used topics

Loading…