1. STT592: Intro. to Statistical Learning
Course Miscellany
Chapter 00

2. STT592: Intro. to Statistical Learning
To do list
1. Try-R from code-school;
2. Create Google drive accounts & folders
3. Select a published paper for scientific writing template and assigned for reading.

3. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Q1: How to name your PPTs, HWs, or project reports?
A1: Use LastName_Project-title.
Eg: Chen_HW1.docx.
Eg: Chen_Wang_Presentation1.pptx.

4. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Q2: Where to submit your PPTs, HWs, or project reports?
A2: Use Google Drive class share-folder.
For Computational projects, ALL computational codes need to be saved into separated files, which will be submitted with project reports and your DATA simultaneously into the folders. Please create your own sub-folder.
Put into desired Google Drive subfolder.

5. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Q3: How to typeset your HWs, or project reports?
A3: Use Word file or Latex. Either will work.
You MUST follow the templates provided for this class from below or from class website.
Conference paper template:
CVPR-Paper word template
CVPR-Paper Latex template (zip files)

6. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Q4: How to typeset equations for projects?
A4: Use Microsoft Equation 3.0, or Latex.
To get to Equation 3.0:
Click on:
Insert Object  Object  Look for Microsoft Equation 3.0.

7. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Q5: Which software should I use for projects?
A5: Any software will work.
R will be the focus for this class, but you can use Python, Excel, Matlab, SAS, or SPSS…, if you can make it work yourself.
Q6: Can I submit my HWs/Projects through s?
A6: Any HW files submitted through s will NOT be accepted.

8. STT592: Intro. to Statistical Learning
Miscellany: Q & A
Basic Ideas...:
HW/Project assignments will be sent out through s.
Some students find it easier to bring your own laptop to daily classes. But it is not required.
Facebook contains extra-curricula materials for Artificial Intelligence (AI) and Data Mining. The access is not required.