Spam Detection in Email using Machine Learning
As an information security analyst, email is a very important tool for communication. One important feature to ensure effective communication is spam filtering. How exactly does the spam filtering system work? Is it possible to build a more effective spam filtering system from scratch?
Technologies & Tools
If you want to view the deployed model, click on the following link:
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| File | Before | After | Percent reduction | |:--|:--|:--|:--| | /static/images/Results/ham-test-2.png | 85.79kb | 57.86kb | 32.56% | | /static/images/Results/spam-test-2.png | 74.67kb | 50.54kb | 32.32% | | /static/images/Results/spam-test-1.png | 110.53kb | 76.27kb | 31.00% | | /static/images/shehan_logo_1000px.png | 56.69kb | 39.76kb | 29.86% | | /static/images/Results/ham-test-1.png | 97.61kb | 68.52kb | 29.80% | | /static/favicon-32x32.png | 1.47kb | 1.22kb | 16.51% | | /static/images/Spam Detection in Email using Machine Learning.png | 655.67kb | 566.69kb | 13.57% | | /static/images/about.jpg | 203.25kb | 187.85kb | 7.58% | | /static/images/testimonial/01.jpg | 86.26kb | 82.55kb | 4.31% | | /static/images/bg/2.jpg | 1,038.58kb | 1,025.27kb | 1.28% | | | | | | | Total : | 2,410.53kb | 2,156.53kb | 10.54% |
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