hands-on tutorial
Hands-on for 'Introduction to Machine Learning using R' tutorial
The questions this addresses are:
- What are the main categories in Machine Learning algorithms?
- How can I perform exploratory data analysis?
- What are the main part of a clustering process?
- How can a create a decision tree?
- How can I assess a linear regression model?
The objectives are:
- Understand the ML taxonomy and the commonly used machine learning algorithms for analysing -omics data
- Understand differences between ML algorithms categories and to which kind of problem they can be applied
- Understand different applications of ML in different -omics studies
- Use some basic, widely used R packages for ML
- Interpret and visualize the results obtained from ML analyses on omics datasets
- Apply the ML techniques to analyse their own datasets
Licence: Creative Commons Attribution 4.0 International
Keywords: statistics, interactive-tools
Target audience: Students
Resource type: hands-on tutorial
Contributors: Erasmus+ Programme, Fotis E. Psomopoulos
Scientific topics: Statistics and probability
Activity log
