mirror of
https://github.com/Andreaierardi/Master-DataScience-Notes.git
synced 2024-07-08 06:31:42 +02:00
21 lines
1.0 KiB
Markdown
21 lines
1.0 KiB
Markdown
# 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
|
|
|