# Statistical Principles in Machine Learning for Small Biomedical Data

Date: **Tuesday 13 December 2022, 9:00-12:00**

Room: **Python (room 2269), Ole-Johan Dahls hus (OJD)**

Instructors: Manuela Zucknick (main), Theophilus Asenso and Chi Zhang

# Welcome!

- The goal of the workshop is to introduce kep concepts in machine learning, such as regularisation.
- The workshop is intended for students and researchers who are interested in applying machine learning methods to
**small data**(few samples, but potentially many features) or**noisy data**(e.g. biomedical data) - Workshop material can be found in the workshop github repository.

#### Learning Objectives

At the end of the tutorial, participants will be able to

- understand key concepts for training machine learning models such as regularisation;
- understand how to incorporate data structure in the regularisation process.

#### Pre-requisites

- Basic familiarity with R
- Introductory level statistics, including regression

# Schedule

Time | Topic | Presenter |
---|---|---|

Now | Preparations | |

9:00 - 10:00 | (Supervised) machine learning with small data | Manuela Zucknick |

R lab 1 | Manuela Zucknick | |

10:15 - 11:15 | Overfitting, regularisation and all that | Manuela Zucknick |

R lab 2 | Manuela Zucknick | |

11:30 - 12:00 | Outlook: Hierarchical models and structured penalties | Theophilus Asenso |