End to End Machine Learning Spam-classification

A cursory look at the web app

Table of Content

• Introduction
• Directories structure
• Programming language
• Dependencies
• Data Processing
• Exploratory data analysis
• Summary
• Acknowledgments
• Instruction on how to run the program locally from your computer
• Run app on the web
• Associated post
• References

Introduction

Directories structure

├── EDA
│   └── Spam_classification.ipynb
├── Read_me_files
│   ├── app_record.gif
│   ├── app_record.webp
│   ├── spam_class.PNG
├── app
│   ├── __init__.py
│   ├── __init__.py
├── data
│   ├── SMSSpamCollection
│   ├── process.py
│   └── readme
├── models
│   ├── model.pkl
│   ├── model.pkl
│   └──  preprocessor.pkl
├── static
│   ├── spam.webp
│   ├── spam_id.ico
│   ├── styles.css
│   └──  thumb_up.webp
├── templates
│   ├── go.html
│   └── master.html
│
├── Procfile
├── README.md
├── Procfile
├── process.py
├── README.md
├── requirements.txt
├── run.py
└── train.py

Programming language

• Python

Dependencies

• Markdown==3.1.1
• matplotlib==3.1.1
• scikit-learn==0.21.3
• seaborn==0.9.0
• autopep8==1.5.3
• click==7.1.2
• flake8==3.8.3
• Flask==1.1.2
• itsdangerous==1.1.0
• Jinja2==2.11.2
• joblib==0.16.0
• MarkupSafe==1.1.1
• mccabe==0.6.1
• nltk==3.5
• numpy==1.19.0
• pandas==1.0.5
• pycodestyle==2.6.0
• pyflakes==2.2.0
• python-dateutil==2.8.1
• pytz==2020.1
• regex==2020.6.8
• scikit-learn==0.23.1
• scipy==1.5.1
• six==1.15.0
• threadpoolctl==2.1.0
• Werkzeug==1.0.1
• wget==3.2

Data Processing

Exploratory data analysis

Summary

Acknowledgments

• Thanks to UCI Machine Learning Repository for making the data available for free.

Instruction on how to run the program locally from your computer

• Navigate to the app directory then type:

• python run.py

Run app on the web

• To run the app globally visit the web app link provided below Click here to view the app

Part of the dependencies

Associated post

References