{"id":15132640,"url":"https://github.com/chandkund/sms-spam-detection","last_synced_at":"2026-01-19T18:02:28.193Z","repository":{"id":257608088,"uuid":"858789893","full_name":"chandkund/SMS-Spam-Detection","owner":"chandkund","description":"The goal is to develop a classification model that can accurately differentiate between spam and non-spam messages. 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The goal is to develop a classification model that can accurately differentiate between spam and non-spam messages. This is crucial for applications like email filtering, SMS spam detection, and improving overall user experience by reducing the influx of unwanted or malicious content.  \n \n### Dataset    \n     \nThe dataset used for this project consists of five columns:    \n1. **v1**: Indicates whether the message is \"ham\" (non-spam) or \"spam\".       \n2. **v2**: Contains the text message.      \n3. **Unnamed: 2**, **Unnamed: 3**, **Unnamed: 4**: These columns are empty or contain irrelevant data and will be ignored in the analysis.                                                                                                           \n            \nSample data:  \n``` \n0    ham    Go until jurong point, crazy.. Available only ...\n1    ham    Ok lar... Joking wif u oni...\n2    spam   Free entry in 2 a wkly comp to win FA Cup fina...\n3    ham    U dun say so early hor... U c already then say... \n4    ham    Nah I don't think he goes to usf, he lives aro...\n```\n\n\n# Spam Detection Project\n\n## Overview\nThis project aims to build a machine learning model that detects whether a given message is spam or not. The dataset contains labeled messages as either \"ham\" (non-spam) or \"spam\". By leveraging natural language processing (NLP) techniques, this project strives to build a robust classifier that can automatically filter out spam messages.\n\n## Dataset\nThe dataset consists of 5 columns:\n- **v1**: Spam or Ham (Target)\n- **v2**: Message text\n- **Unnamed: 2**, **Unnamed: 3**, **Unnamed: 4**: Unused or irrelevant data.\n  \nSample messages:\n- \"ham\": Go until jurong point, crazy.. Available only in bugis n great world...\n- \"spam\": Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005...\n\n## Installation\nClone the repository and install the required dependencies:\n```bash\ngit clone https://github.com/chandkund/SMS-Spam-Detection.git\ncd SMS-Spam-Detection\npip install -r requirements.txt\n```\n\n## Usage\n1. Preprocess the data:\n   - Remove irrelevant columns and missing values.\n   - Tokenize and vectorize the text data using methods like TF-IDF.\n2. Train the classifier:\n   - Use machine learning algorithms such as Naive Bayes or Logistic Regression.\n   - Evaluate the model's performance using metrics like accuracy and F1 score.\n  \n\n3. Predict spam messages:\n```bash\npython predict.py --message \"Free entry to win cash prizes!\"\n```\n\n\n## License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandkund%2Fsms-spam-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchandkund%2Fsms-spam-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandkund%2Fsms-spam-detection/lists"}