(sec:RootMiniProjects.md)=
# Overview of TALENT mini-projects

The exercises in this section are multi-part but are not full-blown projects, hence the name "mini-projects". They originated with the TALENT ("Training in Advanced Low-Energy Nuclear Theory") course given by the authors in 2019.

The contents are:
* [](./mini-project_I_toy_model_of_EFT.ipynb). The goal is to reproduce Bayesian parameter estimation results for a (published) toy model ofeffective field theories, which takes the form of Taylor series of a specified function. 
* [](./model-selection_mini-project-IIa.ipynb) and [](./model-selection_mini-project-IIb_How_many_lines_ptemcee.ipynb) explore model selection via evidence calculation, using as prototypical problems the number of terms in a Taylor series that provide the best to some (noisy) data in a finite range and inferring how many signal peaks there are in a noisy set of data.  
* [](./mini-project_IIIa_bayesian_optimization.ipynb) explores using Bayesian optimization to minimize functions of one variable and more variables while [](./mini-project_IIIb_Bayesian_neural_networks_from_demo.ipynb) explores a basic classification taks with a Bayesian neural network.