Machine Learning and Stanley
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01. Intro to Classifiers
02. ML in The Google Self-Driving Car
03. Stanley Terrain Classification
04. Speed Scatterplot: Grade and Bumpiness
05. Speed Scatterplot 2
06. Speed Scatterplot 3
07. From Scatterplots to Predictions
08. From Scatterplots to Predictions 2
09. From Scatterplots to Decision Surfaces
10. A Good Linear Decision Surface
11. Transition to Using Naive Bayes
12. NB Decision Boundary in Python
13. Getting Started With sklearn
14. Gaussian NB Example
15. GaussianNB Deployment on Terrain Data
16. Calculating NB Accuracy
17. Training and Testing Data
18. Naive Bayes Strengths and Weaknesses
19. Congrats on Learning Naive Bayes
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18. Naive Bayes Strengths and Weaknesses
Naive Bayes Strengths and Weaknesses