Email Spam Detection

➲ Project description

Email spam detection system is used to detect email spam using Machine Learning technique called Natural Language Processing and Python, where we have a dataset contain a lot of emails by extract important words and then use naive classifier we can detect if this email is spam or not.

➲ Prerequisites

This is list of required packages and modules for the project to be installed :

• Python 3.x
• Pandas
• Numpy
• Scikit-learn
• NLTK

Install all required packages :

 pip install -r requirements.txt

➲ The Dataset

Human activites dataset contain about 5728 record which is a sample of an email and a target column "spam" which describe the state of an email spam or not.

➲ Coding Sections

In this part we will see the project code divided to sections as follows:

• Section 1 | The Data :
  In this section we aim to do some operations on the dataset before training the model on it, processes like :

  1. Data Loading : Load the dataset
  2. Data Visualization : Visualize dataset features
  3. Data Cleaning : Remove stopwords and duplicates values
  4. Data Splitting : Split the dataset into training and testing sets
     
     

• Section 2 | The Model :
  The dataset is ready for training, so we create a naive classifier using scikit-learn and thin fit it to the data, and finally we evaluate the model by getting accuracy, classification report and confusion matrix
  

➲ Installation

1. Clone the repo

   git clone https://github.com/omaarelsherif/Email-Spam-Detection-Using-Machine-Learning.git

2. Open 'main.ipynb' in Google Colab or VScode and enjoy

➲ References

These links may help you to better understanding of the project idea and techniques used :

1. Spam detection in machine learning : https://bit.ly/3nwiKtA
2. Naive-bayes algorithm : https://bit.ly/3zc9SLH
3. Model evaluation : https://bit.ly/3B12VOO

➲ Contact

• E-mail : omaarelsherif@gmail.com
• LinkedIn : https://www.linkedin.com/in/omaarelsherif/
• Facebook : https://www.facebook.com/omaarelshereif