# Statistical-Learning-Project

# Exam 
The exam consists in two assignments, one on the first part(regression, tree, neural nets) and the second part (unsupervised learning). For both you must prepare a writing report using one or more techniques and comparing their performance on one or more data set chosen by the student. A brief oral presentation of the reports will be asked. 

Each report must contain:

- short **abstract**: what are your going to present in the report
- **statement** of the problem/**goal** of the analysis and description of the **data set**(s)
- list of three to five **findings/keypoints**
- the analysis with **wise** commentary
- (optional) theoretical background of the used methods
- **conclusions**(should include the findings/keypoints)
- the **Appendix**, containing all the R code

Notice:
- The **paper length** is irrelevant provided that the content is correct.
- **No R code in the main text**. The R code must be confined to the appendix
- The report should be prepared in **PDF** only