Download this code from https://codegive.com Title: Implementing Naive Bayes Classifier in Python - A Step-by-Step Tutorial Introduction: Naive Bayes classifiers are powerful probabilistic algorithms used in machine learning for classification tasks. In this tutorial, we will walk through the implementation of a Naive Bayes classifier in Python and share the code on GitHub for easy access and collaboration. Prerequisites: Step 1: Setting Up the Project on GitHub Step 2: Installing Required Libraries Ensure you have the necessary libraries installed. If not, install them using: Step 3: Creating the Naive Bayes Classifier Create a new Python file (e.g., naive_bayes_classifier.py) and implement the classifier using the following code: Step 4: Committing Changes to GitHub Commit your changes and push them to your GitHub repository: Conclusion: Congratulations! You have successfully implemented a Naive Bayes classifier in Python and shared the code on GitHub. This tutorial provides a foundation for further exploration and enhancements in the field of text classification. Feel free to customize the code to suit your specific use case and data. ChatGPT