Intro to Naive Bayes Classifiers

Learn the fundamentals of Naive Bayes, implement classifiers in Python, and apply them to real-world problems.
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Bayes' Theorem and Naive Bayes Fundamentals

Unit 1: Bayes' Theorem: The Foundation

Unit 2: Naive Bayes: Simplifying Assumptions

Unit 3: Building a Naive Bayes Classifier

Types of Naive Bayes Classifiers

Unit 1: Gaussian Naive Bayes

Unit 2: Multinomial Naive Bayes

Unit 3: Bernoulli Naive Bayes

Unit 4: Choosing the Right Classifier

Implementation and Evaluation

Unit 1: Data Preparation for Naive Bayes

Unit 2: Implementing Naive Bayes with Scikit-learn

Unit 3: Evaluating Naive Bayes Models

Unit 4: Improving Model Performance

Applications and Comparison

Unit 1: Real-World Applications of Naive Bayes

Unit 2: Naive Bayes vs. Other Algorithms

Unit 3: Advantages and Limitations