Master-DataScience-Notes/1year/3trimester/Machine Learning, Statistical Learning, Deep Learning and Artificial Intelligence/Statistical Learning, Deep Learning and Artificial Intelligence/Project/README.md

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