Spam, or unwanted commercial or mass e-mail, has recently become a major issue on the internet. Spam is a waste of time, storage space, and data transfer capacity.
Naive Bayes classifiers are a popular statistical strategy for e-mail filtering. They commonly use a bag of words feature to identify spam e-mail. As a consequence, we'll build a rudimentary message classifier using the Naive Bayes theory.
Make sure that you have the following:
- Python 3+ and pip (which comes with Python 3+)
- sklearn
- pandas
- flask
- An environment to work in - something like Jupyter or Spyder
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Clone the repo
git clone https://github.com/meetgajjarx07/Spam-Classification-Flask
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Install Python packages
pip install flask pip install scikit_learn pip install pandas
OR
pip install -r requirements.txt
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Run Spam_Classifier_Main File
python Spam_Classifier_Main.py
Distributed under the MIT License. See LICENSE.txt for more information.