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We receive emails that are not advantageous to us and can be misleading and dangerous; We have no idea what damage is lurking behind them. This project assists us in avoiding potentially hazardous emails by screening them.

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Adarsh275/Email-Spam-Detection-System

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Email-Spam-Detection-System

Project Pathners

Adarsh Kumar------SRN: PES2UG20CS016 Sreekar Govind----SRN: PES2UG20CS125 Aryaman Yadav-----SRN: PES1UG20CS079

These are the parts of our project:

1st PART

->In this we tried to check the Accuracy and Pression of the different algorithms.

FILES USED:

Folder: Filtering_Accuracy_Checking
-> email-spam-filtering-project.ipynb
-> completeSpamAssassin.csv

STEPS TO RUN OUR PROJECT:

  • Put the code in Google Collab Cells/Jupyter/kaggle
  • Import the data set that consist of Spam & Non-Spam Emails
  • Then run each cell one by one It might take some time to run

2nd PART

FILES USED:

Folder: Filtering_GUI_SVM_Model
-> SVM_GUI_Filtering.py
-> spam.csv

This part we our self-implemented a SVM algorithm and GUI Part was created with the help of Python Library tkinter.

STEPS TO RUN OUR PROJECT:

  • As we know that tkinter is not present in google Collab so we have to run this on our personal system.
  • Make a folder and put code file there and also put data set file in that same folder. If you want to chance the path simply update the path in code file as well.
  • The run the python code.
  • A box will appear, you have to some the in it and click check button it say weather that is ham or spam.

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We receive emails that are not advantageous to us and can be misleading and dangerous; We have no idea what damage is lurking behind them. This project assists us in avoiding potentially hazardous emails by screening them.

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