Spam Filter In Python3

This basically my Sophomore Year Project in which I had to detect the mail is spam or not according to the specific keywords found in the mail.
It basically checks the keywords from the .csv and train its models that the predicts the result that the mail will be the spam or not.
The basic level of the prediction in the dataset varies from the 88% to 86% respectively.
class SpamClassifier(object) is basically putting the keywords in form of list and then trains the models according to the model.

Getting Started

First Download the Dataset from the link given in the Data Sources.
Clone the repo
Go to the File and run the .py file through cmd with python3 as the default python version.

How Things Are Working

First we had cleaned the dataset and deleted some of the columns from the dataset so that we can filter the important vs unimportant.
Changed the name of the Columns according to the Dataset we had got.
class SpamClassifier(object): It is basically takes the input as an object and train the model to find the keywords is spam or not.
Tkinter is basically used for the showing the answer in the input box form as the Mail is Good Email or Spam Email.

Technologies:

Programming Language: Python3
Libraries: Pandas, Scikit-learn, Matplotlib, Seaborn
Visualization:Plotly and Numpy

Data Sources:

Datasets used for the analysis can be found on the given link.

Prerequisites

What things you need to install the software and how to install them

pip install python3

You should already need to have all the dependencies so that you will be able to check the email is spam or not given in the Visualization row of the Technologies Section.

Built With

VisualStudio Code - Best Editor for the Code Writing and Debugging
Python - All the dependecy are used on Python3
Kaggle For The Spam Dection Dataset -Get the Dataset from here.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

Rahul Chandra - Initial work - Machine Learning Enthusiast

Linux Humour:

Don't forget to check the Linux Humour Folder because I truly believe that Humour is necessary in our life and we can only achieve the success in the life when we have postive attitude about the life and work.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

Works on only with the Python3 dependencies(so please take care of it)
Practiced how to work on the Exploratory Data Analysis Techniques)

irahulcse/Spam_Filter