Project: Naive Bayes Tutorial

Spervised Learning, Classification

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Table Of Contents:

• Description
  
  • About the project
    
• Data
  
  • Files
    
  • Dataset file
    
• Loading Project
  
  • Requirements
    
  • Execution
    

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Description

About the project

In this project we need to predict whether a message is spam or ham/not spam with Naive Bayes Classifier. This project will guide us through how to use Bag of Words and Naive Bayes step by step and understand its intuition and how its implemented along the way.

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Data

Files

This project contains 2 files and 2 folder:

• report.ipynb: This is the main file where I have performed my work on the project.
• data: The project dataset. I have loaded this data in the notebook..
• export/ : Folder containing HTML and PDF version file of notebook.
• images/ : Contains Images which are displayed in report.ipynb file.

Dataset file

data file, contains 500+ instances on whether a particular message is spam or not spam / spam or ham.

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Loading Project

Requirements

This project requires Python 3.6 and the following Python libraries installed:

• Python 3.6.6 (Language Used for the project)
• Pandas (For Data Analysis)
• scikit-learn (ML Library for Python)

You will also need to have software installed to run and execute a Jupyter Notebook

If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included.

Execution

In a terminal or command window, navigate to the top-level project directory Naive_Bayes_Tutorial (that contains this README) and run one of the following commands:

ipython notebook report.ipynb

or

jupyter notebook report.ipynb

This will open the Jupyter/iPython Notebook software and project file in your browser.

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