Bunch of exercises computed during the Machine Learning for Finance course. Different themes are covered:
- KNN and OLS for digit identification problem.
- Logistic Regression.
- Linear Discriminant Analysis (LDA).
- Quadratic Discriminant Analysis (QDA).
- Non-parametric bootstrap.
- Bootstrap Confidence Intervals.
For the first theme we use files GZ called zip.test and zip.train. For the others, we use the a CSV file called NASA.
I have uploaded two files for the result. One is a Rmarkdown file and the other one is a R script file (Raw_file). I suggest to use the Rmd file converting it into a HTML file. In this way you will be able to watch the graphs and photos.