Support Vector Machines
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01. Welcome to SVM
02. Separating Line
03. Choosing Between Separating Lines
04. Maximizing the Margin
05. Practice with Margins
06. SVMs and Tricky Data Distributions
07. SVM Response to Outliers
08. SVM Outlier Practice
09. Handoff to Katie
10. SVM in SKlearn
11. Coding Up the SVM
12. Nonlinear SVMs
13. Nonlinear Data
14. A New Feature
15. Visualizing the New Feature
16. Separating with the New Feature
17. Practice Making a New Feature
18. Kernel Trick
19. Playing Around with Kernel Choices
20. Kernel and Gamma
21. SVM C Parameter
22. SVM Gamma Parameter
23. Overfitting
24. SVM Strengths and Weaknesses
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18. Kernel Trick
Kernel Trick