- Lecture notes
- Should be accessible via https://cforssen.gitlab.io/learningfromdata/.
- This is a Jupyter Book for which the source material is available in a gitlab repository. Alternatively, you can download individual chapters in various formats. Some chapters are based on Jupyter Notebooks that you can download and play with yourself.
- The set of notes is quite extensive and also covers more traditional machine learning (including neural networks and Gaussian processes).
- In this lecture series we will focus on the Bayesian parts with a nuclear-physics perspective.
- The notes will be updated. Some chapters are still work in progress.
- Reading guide
- For a reminder on statistics concepts, see chapter 6.
- The first lectures will focus on the "Bayesian methods for scientific computing" part.
- We will use python for the exercise sessions. You are welcome to test your python skills with the exercise notebooks in the Introduction part.
- Python environment
- See the installation instructions.