{"id":21951541,"url":"https://github.com/jeus0522/ml-project-email-spam-classifier","last_synced_at":"2026-05-20T14:09:38.068Z","repository":{"id":253107352,"uuid":"839085381","full_name":"jeus0522/ML-Project-Email-Spam-Classifier","owner":"jeus0522","description":"ML project focused on email spam classification, demonstrating data preprocessing, model training, and evaluation using Python and scikit-learn.","archived":false,"fork":false,"pushed_at":"2024-08-07T00:35:52.000Z","size":2765,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-03T22:37:37.163Z","etag":null,"topics":["data-science","eda","email-classification","machine-learning-projects","nlp","spam-classification","text-classification"],"latest_commit_sha":null,"homepage":"https://email-sms-classifier-by-emon.onrender.com/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jeus0522.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-08-07T00:07:59.000Z","updated_at":"2024-10-18T17:05:37.000Z","dependencies_parsed_at":"2024-08-14T14:27:34.329Z","dependency_job_id":"3df54f3e-6473-4179-8460-73b116cd2309","html_url":"https://github.com/jeus0522/ML-Project-Email-Spam-Classifier","commit_stats":null,"previous_names":["jeus0522/ml-project-email-spam-classifier"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeus0522%2FML-Project-Email-Spam-Classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeus0522%2FML-Project-Email-Spam-Classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeus0522%2FML-Project-Email-Spam-Classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeus0522%2FML-Project-Email-Spam-Classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jeus0522","download_url":"https://codeload.github.com/jeus0522/ML-Project-Email-Spam-Classifier/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244999230,"owners_count":20544866,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","eda","email-classification","machine-learning-projects","nlp","spam-classification","text-classification"],"created_at":"2024-11-29T06:14:57.426Z","updated_at":"2026-05-20T14:09:38.061Z","avatar_url":"https://github.com/jeus0522.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Project: Email Spam Classifier\n\nWelcome to the **Email Spam Classifier** machine learning project repository! This project focuses on classifying emails as spam or non-spam (ham) using various machine learning techniques.\n\n![email](https://github.com/user-attachments/assets/bb235a1a-ffcb-46a3-8023-2f1625f86fbf)\n\n## 📋 Contents\n\n- [Introduction](#introduction)\n- [Why This Project](#why-this-project)\n- [Dataset](#dataset)\n- [Features](#features)\n- [Models Implemented](#models-implemented)\n- [Evaluation Metrics](#evaluation-metrics)\n- [Setup and Installation](#setup-and-installation)\n- [Demo](#demo)\n- [Contributing](#contributing)\n- [Challenges Faced](#challenges-faced)\n- [Lessons Learned](#lessons-learned)\n- [License](#license)\n- [Contact](#contact)\n\n---\n\n## 📖 Introduction\n\nThis repository contains a machine learning project focused on classifying emails as spam or non-spam using supervised learning techniques. It includes data preprocessing, model development, evaluation, and deployment aspects of the project.\n\n---\n\n## 🎯 Why This Project\n\nThe primary motivation behind creating this project is to tackle the issue of email spam, which remains a significant problem affecting users' productivity and security. By accurately classifying emails, this project aims to improve email filtering systems.\n\n---\n\n## 📊 Dataset\n\nThe dataset used for this project contains a collection of emails labeled as spam or ham. It includes various features extracted from the emails, such as text content, subject line, sender information, etc.\n\n---\n\n## 🌟 Features\n\n- **Data Preprocessing:** Cleaned and transformed dataset for machine learning model compatibility.\n- **Model Development:** Trained multiple machine learning models to classify emails as spam or ham.\n- **Model Evaluation:** Evaluated models using appropriate metrics to ensure accuracy and reliability.\n- **Deployment:** Implemented a simple web-based or command-line application for classifying new emails.\n\n---\n\n## 🧠 Models Implemented\n\nSeveral machine learning models were implemented and evaluated:\n\n- Naive Bayes Classifier\n- Support Vector Machine (SVM)\n- Random Forest Classifier\n- Logistic Regression\n- others\n\nEach model's performance was compared based on metrics such as accuracy, precision, recall, and F1-score.\n\n---\n\n## 📊 Evaluation Metrics\n\nThe models were evaluated using the following metrics:\n\n- **Accuracy:** Overall correctness of the predictions.\n- **Precision:** Proportion of true positives among all positive predictions.\n- **Recall:** Proportion of true positives identified correctly.\n- **F1-score:** Harmonic mean of precision and recall, providing a balance between the two metrics.\n\n---\n\n## 🚀 Setup and Installation\n\nTo run this project locally, follow these steps:\n\n1. Clone the repository:\n\n   ```bash\n   git clone https://github.com/Md-Emon-Hasan/ML-Project-Email-Spam-Classifier.git\n   ```\n\n2. Navigate to the project directory:\n\n   ```bash\n   cd ML-Project-Email-Spam-Classifier\n   ```\n\n3. Install the required dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n4. Run the notebooks or scripts as per your requirements.\n\n---\n\n## 🌐 Demo\n\nExplore the live demo of the project [here](https://email-sms-classifier-by-emon.onrender.com) \n\n---\n\n## 🤝 Contributing\n\nContributions to enhance or expand the project are welcome! Here's how you can contribute:\n\n1. **Fork the repository.**\n2. **Create a new branch:**\n\n   ```bash\n   git checkout -b feature/new-feature\n   ```\n\n3. **Make your changes:**\n\n   - Implement new features, improve model performance, or enhance documentation.\n\n4. **Commit your changes:**\n\n   ```bash\n   git commit -am 'Add a new feature or update'\n   ```\n\n5. **Push to the branch:**\n\n   ```bash\n   git push origin feature/new-feature\n   ```\n\n6. **Submit a pull request.**\n\n---\n\n## 🛠️ Challenges Faced\n\nDuring the development of this project, the following challenges were encountered:\n\n- Handling text data preprocessing, including tokenization and feature extraction.\n- Dealing with class imbalance in the dataset.\n- Optimizing model performance and scalability.\n\n---\n\n## 📚 Lessons Learned\n\nKey lessons learned from this project include:\n\n- Importance of feature selection and engineering in text classification tasks.\n- Evaluation and selection of appropriate metrics based on project goals.\n- Deployment considerations for machine learning models in real-world applications.\n\n---\n\n## 📄 License\n\nThis project is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for more details.\n\n---\n\n## 📬 Contact\n\n- **Email:** [iconicemon01@gmail.com](mailto:iconicemon01@gmail.com)\n- **WhatsApp:** [+8801834363533](https://wa.me/8801834363533)\n- **GitHub:** [Md-Emon-Hasan](https://github.com/Md-Emon-Hasan)\n- **LinkedIn:** [Md Emon Hasan](https://www.linkedin.com/in/md-emon-hasan)\n- **Facebook:** [Md Emon Hasan](https://www.facebook.com/mdemon.hasan2001/)\n\nFeel free to reach out for any questions or feedback regarding the project!\n\n---\n\nFeel free to adjust and customize this template to better fit your project's specific details and style preferences.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeus0522%2Fml-project-email-spam-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjeus0522%2Fml-project-email-spam-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeus0522%2Fml-project-email-spam-classifier/lists"}