Description#
- Developed a SMS spam detection project using machine learning techniques.
- Utilized a dataset containing labeled examples of spam and non-spam messages.
- Implemented data preprocessing steps to clean and prepare the text data for analysis.
- Explored various machine learning algorithms, such as Logistic regression, Support Vector Machines, etc for classification.
- Split the dataset into training and testing sets to evaluate the model’s performance.
- Successfully identified and classified SMS messages as spam or non-spam with accuracy of about 89%.