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| 15:00 - 16:30 |**Supervised Learning** <br /><br /> **_Classification_**. <br /> - How could supervised learning be used to analyze omics data. <br /> **_Regression_**. <br /> - What if the target variable is numerical rather than categorical? <br /> [_Link to material_](episodes/04-supervised-learning.md)|
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| 16:30 | Closing, discussion and resource sharing|
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## Other examples
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If you finish all the exercices and wish to practice on more examples, here are a couple of good examples to help you get more familiar with the different ML techniques and packages.
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1.[RNASeq Analysis in R](https://combine-australia.github.io/RNAseq-R/06-rnaseq-day1.html)
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2.[Use the Iris R built-in data set](https://github.com/fpsom/CODATA-RDA-Advanced-Bioinformatics-2019/blob/master/3.Day3.md)to run clustering and also some supervised classification and compare results obtained by different methods.
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## Sources / References
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The material in the workshop has been based on the following resources:
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