Skip to main content
Back to top
Ctrl
+
K
Welcome to DS325 Applied Data Science
Setting Up and Resources
Setting Up
Pandas Refresher
Regression
1. What is a model?
2. Linear Regression (Part 1)
2.3. Example: Simple Linear Regression with the King County Housing Dataset
2.4. Example: Multiple Linear Regression Estimating Fuel Efficiency
3. Regularization
4. Polynomial Regression
4.3. Example: King County Housing
4.4. Example: West Claude University
5. Chapter 1 - The Machine Learning Landscape
Classification
7. Classification
8. Encoding
9. Trees and Ensemble methods
10. Tree Methods (continued)
11. Forests and Trees
12. PS04 - Comparing Tree Methods
Unsupervised Learning
13. Principle Component Analysis (PCA)
14. PCA: Examples and Observations
15. K-Means Clustering
16. K-Means Clustering: An Animated Walkthrough
Assignments
PS01 - Simple Linear Regression
PS02 - Regularization
PS03 - Classification
Index
