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1
Introduction
2
Probability
3
Probability and Events
4
Probability Example
5
Bayes Theorem and Rule
6
Naive Bayes Application Example
7
Naive Bayes Classifier
8
Demo#1 in R
9
Models to Predict How Lawmakers may Vote
10
Demo#2 in R
11
Models to Predict Diabetes in Patients
12
Demo#3 in R
13
QnA
Description:
Dive into a comprehensive 1-hour 23-minute webinar on Naive Bayes Classification, exploring its applications in facial recognition, weather prediction, medical diagnoses, and news classification. Learn the fundamentals of probability, Bayes Theorem, and the Naive Bayes Classifier through theoretical explanations and practical coding examples in R. Gain insights into real-world applications, including predicting lawmaker voting patterns and diagnosing diabetes. By the end, acquire a strong understanding of this powerful machine learning technique, complete with hands-on demonstrations and a Q&A session to solidify your knowledge.

Crash Course on Naive Bayes Classification

Data Science Dojo
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