Naive Bayes Algorithm in Machine Learning | Naive Bayes Tutorial | Tutorialspoint

In this tutorial on 'Machine Learning', you will learn about Naive Bayes Algorithm.
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Timestamps
0:30 What is Naive Bayes?
0:56 Introducing Bayes Theorem
1:49 Bayes Theorem Example
2:58 Bayes Theorem Working
6:35 Applications
6:47 Advantages

Naive Bayes is a classification technique based on Bayes theorem with an independence assumption among predictors. Naive bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.
In this series you will learn all types of Machine Learning Algorithms, Supervised Learning, Unsupervised Learning, Reinforcement Learning, KNN, Decision Tree, Linear Regression, Support Vector Machine, Random Forest, Naive Bayes, Logistic regression, K means clustering, Hierarchical clustering, Anomaly detection, Q learning, Deep Q Networks, and more.

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[lightway]

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