Originally the Statistical Learning Group (SLG) was created to fill a gap in advanced statistical areas of interest not typically covered in coursework, and we intend to continue this mission. We propose to form a reading group of graduate and highly motivated undergraduate students to learn more about Deep Learning, and where possible, connect statistical ideas. To accomplish this we will select a text (or a few texts) to read from, and answer directed questions, which we will discuss in our meetings. In an effort to better facilitate learning when the group meets one member will give a low-stakes presentation on the topic from the reading; this presentation can be thought of as a short 5-minute lightning talk.
Reading Deep Learning With R by Chollet and Allaire
- This book utilizes the Keras package
- Another book you may find useful is Deep Learning by Goodfellow, Bengio, and Courville
Meetings roughly every other Thursday 12pm-1 in SAS 1105. General structure:
- Chapter Review / Presentation (Lightning talk) ~ 5 Minutes
- Discussion Questions ~ 20 - 30 Minutes
- Kaggle | Presentation | News Article/ Paper ~ 20 - 30 Minutes
Rough schedule:
| Date | Topic | Lightning-Talk Presenter(s) & Links |
|---|---|---|
| Jan 9th | Introduction, Intro to R/GitHub | |
| Jan 16th | Chapters 1 & 2 | David E. & Peter N. |
| Jan 30th | Chapter 3 & Applied Project | Cameron E. & Dale G. |
| Feb 13th | Chapter 4 | Antonio J. |
| Feb 27th | Chapter 5 | Deepak K. |
| Mar 19th | Computer Vision Project | |
| Apr 2nd | Chapter 6 | |
| Apr 16th | Natural Language Processing Project |
- Fork AlvinSheng/SLG-Deep-Learning
- You only have to do this once ever!
- Edit the question document
- Commit to your branch
- If editing in rstudio use the following
- git add -A
- git commit --m "Your message here"
- git push
- Submit a pull request