https://github.com/juzershakir/naive-bayes-tutorial
Getting Intuition behind the implementation of Naive Bayes Classifier with SMS spam collection data.
https://github.com/juzershakir/naive-bayes-tutorial
accuracy bag-of-words classification f1-score machine-learning multinomial-naive-bayes naive-bayes-classifier pandas precision python3 recall scikit-learn sms-spam-detection supervised-learning
Last synced: 8 months ago
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Getting Intuition behind the implementation of Naive Bayes Classifier with SMS spam collection data.
- Host: GitHub
- URL: https://github.com/juzershakir/naive-bayes-tutorial
- Owner: JuzerShakir
- Archived: true
- Created: 2018-10-07T04:40:47.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-10-08T12:42:19.000Z (over 7 years ago)
- Last Synced: 2024-12-18T14:14:36.631Z (over 1 year ago)
- Topics: accuracy, bag-of-words, classification, f1-score, machine-learning, multinomial-naive-bayes, naive-bayes-classifier, pandas, precision, python3, recall, scikit-learn, sms-spam-detection, supervised-learning
- Language: HTML
- Homepage: https://nbviewer.jupyter.org/github/JuzerShakir/Naive-Bayes-Tutorial/blob/master/report.ipynb
- Size: 366 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Project: Naive Bayes Tutorial
## Spervised Learning, Classification
----
### Table Of Contents:
- [Description](#description)
- [About the project](#about-the-project)
- [Data](#data)
- [Files](#files)
- [Dataset file](#dataset-file)
- [Loading Project](#loading-project)
- [Requirements](#requirements)
- [Execution](#execution)
----
### 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.
----
### 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.
----
### Loading Project
#### Requirements
This project requires **Python 3.6** and the following Python libraries installed:
- [Python 3.6.6](https://www.python.org/downloads/release/python-366/) (Language Used for the project)
- [Pandas](http://pandas.pydata.org) (For Data Analysis)
- [scikit-learn](http://scikit-learn.org/stable/) (ML Library for Python)
You will also need to have software installed to run and execute a [Jupyter Notebook](http://jupyter.org/install)
If you do not have Python installed yet, it is highly recommended that you install the [Anaconda](https://www.anaconda.com/download/) 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:
```bash
ipython notebook report.ipynb
```
or
```bash
jupyter notebook report.ipynb
```
This will open the Jupyter/iPython Notebook software and project file in your browser.
-----