SMS Spam Detection

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Context:

The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of text messages in English of 5,574 messages.

Goals:

• Convert text data from unsupervised to supervised and Find the targets.
• Develop a predictive model that can accurately classify which texts are spam.

Dataset sourec:

from Kaggle website [Kaggle]

Algorithms:

• Preprocessing text messages.
• clustering (k-means)
• Naive Bayes
• XGBoost
• Random Forest
• SVM

Tools:

• Libraries: pandas, numpy, matplotlib, seaborn, MLextend, sklearn,XGBoost,Statsmodels.

• Softwares: Trello, GitHub, Jupyter, prize, Zoom, Colaboratory .

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Team Members

• Abdulrahim Alshehri-Leader
• Elham Alzahrani
• Nouf Alkhaldi