Lec-6.26 Bayes Theorem and Naive Bayes Classifier (Arif Butt @ Data Science)
01:17 Learning Agenda
02:20 Bayes Theorem
07:04 Examples of Bayes Theorem
12:20 Overview of Naive Bayes Classifier
13:43 Example 1: Single Discrete Input Feature
20:40 Zero Frequency Problem and Laplace Smoothing
23:20 Example 2: Multiple Discrete Input Features
30:11 Example 3: Multiple Discrete Input Features
33:12 Example 4: Text Data
37:18 Naive Bayes Classifier for Continuous Input Features
37:33 Example 5: Single Continuous Input Feature
44:31 Example 6: Multiple Continuous Input Feature
46:33 Tasks to do
email: [email protected], [email protected], [email protected]
Lecture Slides and Resources: http://arifbutt.me
Jupyter notebooks: https://github.com/arifpucit/data-sci...