Naive Bayes
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01. ML in The Google Self-Driving Car
02. Acerous Vs. Non-Acerous
03. Supervised Classification Example
04. Features and Labels Musical Example
05. Features Visualization Quiz
06. Classification By Eye
07. Intro To Stanley Terrain Classification
08. Speed Scatterplot: Grade and Bumpiness
09. Speed Scatterplot 2
10. Speed Scatterplot 3
11. From Scatterplots to Predictions
12. From Scatterplots to Predictions 2
13. From Scatterplots to Decision Surfaces
14. A Good Linear Decision Surface
15. Transition to Using Naive Bayes
16. NB Decision Boundary in Python
17. Getting Started With sklearn
18. Gaussian NB Example
19. GaussianNB Deployment on Terrain Data
20. Calculating NB Accuracy
21. Training and Testing Data
22. Unpacking NB Using Bayes Rule
23. Bayes Rule
24. Cancer Test
25. Prior and Posterior
26. Normalizing 1
27. Normalizing 2
28. Normalizing 3
29. Total Probability
30. Bayes Rule Diagram
31. Bayes Rule for Classification
32. Chris or Sara
33. Posterior Probabilities
34. Bayesian Probabilities On Your Own
35. Why Is Naive Bayes Naive
36. Naive Bayes Strengths and Weaknesses
37. Congrats on Learning Naive Bayes
38. Naive Bayes Mini-Project Video
39. Getting Started with Mini-Projects
40. Machine Learning for Author ID
41. Getting Your Code Set Up
42. Author ID Accuracy
43. Timing Your NB Classifier
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32. Chris or Sara
Chris or Sara
Question:
Start Quiz:
Solution:
INSTRUCTOR NOTE:
Note that 50% (.5) of Sara's words are
love
.
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