Spam Email Detection

Table of Contents

	Table Of Contents
1	About
2	Setup
3	Libraries
4	Data Set
5	Contributors

Directory Structure

├── Source
│   ├── ML.ipynb
|
├── Report
│   ├── Report.pdf
│
├── Data Set
│   ├── Spam & Ham.csv
│
└── Index.html  
│ 
└── README.md

About

• In our day-to-day life, Spam Emails are considered to be annoying and repetitive, which is solely send for the purpose of advertisement and brand promotion.
• It is one of the most demanding and troublesome internet issues in today’s world of communication and technology.
• Sending malicious link through spam emails which can harm our system and can also seek in into your system.
• Spam emails not only influence the organizations financially but also exasperate the individual email user.
• This project will identify those spam by using techniques of machine learning, where it applies algorithms on our data sets and the best algorithm is selected for the email spam detection having best precision and accuracy.

Setup

• To run this project, install and setup the following Libraries,

!pip install numpy
!pip install scipy
!pip install matplotlib
!pip install pandas
!pip install seaborn
!pip install pillow
!pip install scikit-learn

Libraries

• Project is created with,

  • Matplotlib
  • Pandas
  • Numpy
  • Seaborn
  • Sklearn

Data-Set

Name	Link
Kaggle	Kaggle

Contributors

Harsha Sathish	S Abhishek	Navneet Kumar Singh	Arvind Kumar K