These are the materials for our Kernel Machine learning workshop at the Red Rock Data Science Student Conference at Southern Utah University in 5/2024. Hopefully they are helpful!
- Lots of diverse material and new concepts will be covered in this course
- Machine Learning is NOT a spectator sport! You need to practice the skills you learn over and over again!
- Communication: if you have questions or concerns, please email me: [email protected]
- GitHub materials for the course:
- All materials for this course will be posted on the course GitHub page: https://github.com/wevanjohnson/2024_05_RRDS_ML_Workshop/edit/main/README.md
- You obviously have this since you are here!
- Schedule:
| Topics |
|---|
| Introduction to Machine Learning Terminology |
| Overview of Machine Learning Methods |
Data preparation (the caret package in R) |
| Supervised and unsupervised learning. |
| Kernel-based Methods (particularly SVMs) |
| Decision Trees and Random Forests |
| Neural Networks |
| Code + case studies are integrated throughout |