Instructor: Jonathan Hersh (hersh@chapman.edu)
Hello! These are the materials for the Machine Learning training at the Central Bank of Belize. The topics covered will include:
| Monday, October 24th, 2022 | |
|---|---|
| Time | Topic |
| 8:30 AM | Registration and light breakfast |
| 9:00 AM | Opening remarks – Maria Cecilia Deza (IDB) |
| 9:10 AM | Introductions, participants and instructor |
| 9:30 | 1. Introduction to Machine Learning and R |
| 11:00 AM | Lunch |
| 1:30 PM | 2. Data manipulaton using dplyr |
| 3:00 PM | Coffee break |
| 3:00 PM | 3. Graphing relationships between variables using ggplot2 |
| 5:30 PM | Recap of the day, Q&A |
| Tuesday, October 25th, 2022 | |
|---|---|
| Time | Topic |
| 8:30 AM | Light breakfast |
| 9:00 AM | 4. Linear Regression |
| 10:00 AM | 5. Machine Learning: Lasso, Ridge and ElasticNet |
| 11:00 AM | Coffee break |
| 11:15 AM | 6. Machine Learning: Decision Trees and Random Forests |
| 1:00 PM | Lunch |
| 2:00 PM | 7. Binary Classification Diagnostics |
| 3:30 PM | Coffee break |
| 4:00 PM | 8. Mapping model results in R |
| 5:00 PM | Recap of the day, Q&A |
We will be coding in the R together. I don't presume any knowledge of coding, so don't be afraid if you've never coded before.
There are two ways you can run R and RStudio, either locally on your computer, or on the cloud in rstudio.cloud
If you would like to install and run R locally please install the following programs:
- RStudio Desktop 2022.07.2+576 link
- R 4.2.1 link
- RTools [https://cran.r-project.org/bin/windows/Rtools/rtools42/rtools.html]
If you cannot install those programs, please head over to rstudio.cloud.
- Click "GET STARTED FOR FREE"
- Then click "Sign Up".
- You may log in using your email address
- Next click new project.
- You should now see a R Studio session in your browser.
If you have never used Github, don't worry. You can either clone the repository, or you may click the "Code" button on the main page, and then "Download Zip" to download all the files. You may also download the files individually, or copy and paste code as needed.
install.packages('usethis')
# install.packages('tidyverse')
newProject <- usethis::use_course('https://github.com/jonhersh/Belize_ML_2022/archive/main.zip')