May 23-31, 2022
Official course description: https://phdcourses.ku.dk/DetailKursus.aspx?id=109397&sitepath=SUND
PANUM, Blegdamsvej 3B, 2200 Copenhagen, Maersk Tower, Floor 15, room 7.15.152
Main teacher: Shyam Gopalakrishnan [email protected]
Introduction to ML
| Time | |
|---|---|
| 9-10 | Introduction to Machine Learning |
| 10-11 | Unsupervised learning: PCA |
| 11-12 | PCA exercises |
| 12-13 | Lunch break |
| 13-14 | Supervised learning: classification and regression |
| 14-15 | Logistic regression exercises |
Main teacher: Anders Krogh [email protected]
Neural Networks
| Time | |
|---|---|
| 9-10 | Lecture: What is a NN? Feed-forward NN. Backpropagation. Day2/NNintro1.pdf. Notebook for gradient descent  |
| 10-11 | Exercise: Introduction to Pytorch. Make your first NN |
| 11-12 | Lecture: Issues in training. SGD, Adam. mixed with hands-on. Day2/NNintro2.pdf |
| 12-13 | Lunch break |
| 13-14 | Exercise with gene expression data |
| 14-15 | Lecture: Neural networks for sequences (one-hot encoding, convolution). Performance evaluation (ROC curve). Day2/NNintro3.pdf |
| 15-16 | Exercise on prediction of TSS in DNA sequences |
Main Teacher: Ole Winther [email protected] (morning) Anders (afternoon)
Generative Neural Networks
| Time | |
|---|---|
| 9-10 | Generative Neural Networks |
| 10-12 | Exercise on Generative Neural Networks |
| 12-13 | Lunch break |
| 13-14 | Start project work. See project folder. |
| 14-15 | Talk by Mani Arumugam: Gut microbiome signatures of Colorectal Cancer. (Data set for use in the Hackathon) |
| 15-16 | Continue project |
Main Teacher: Anders
| Time | |
|---|---|
| 9-12 | Continue project work |
| 12-13 | Lunch break |
| 13-15 | Project presentations |
| 15-16 | Reflections, Discussion, Questions, Evaluation |
Responsible: Ruth Loos [email protected] & Cameron MacPherson [email protected]
Talks: Example of machine learning applications in the biomedical field & intro to hackathon
See separate program