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Introduction to machine learning in biomedical research - Part A

May 23-31, 2022

Official course description: https://phdcourses.ku.dk/DetailKursus.aspx?id=109397&sitepath=SUND

Location

PANUM, Blegdamsvej 3B, 2200 Copenhagen, Maersk Tower, Floor 15, room 7.15.152

Course plan

Monday May 23

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

Tuesday May 23

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 Open In Colab
10-11 Exercise: Introduction to Pytorch. Make your first NN Open In Colab
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 Open In Colab
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 Open In Colab

Wednesday, May 25

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

Monday, May 30

Main Teacher: Anders

Time
9-12 Continue project work
12-13 Lunch break
13-15 Project presentations
15-16 Reflections, Discussion, Questions, Evaluation

Tuesday, May 31

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

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