Email Spam Detection Using Machine Learning

[SayantikaLaskar]

Classifying spam mail using machine learning faces several key challenges. Ensuring high accuracy and minimizing false positives and negatives is crucial to avoid misclassifying legitimate emails or missing actual spam. Spammers constantly evolve their tactics, making it difficult for classifiers to keep up. Balancing model complexity with performance and scalability is essential, as more sophisticated algorithms require more resources. Effective feature selection, adapting to user preferences, and addressing legal and ethical concerns around privacy and data security are also critical. Choosing the right machine learning models and obtaining quality training data are necessary for accurate classification. Additionally, integrating the system with existing infrastructure and maintaining it through regular updates are ongoing challenges.

[github-actions[bot]]

Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊

You can also check our CONTRIBUTING.md for guidelines on contributing to this project.

[sonali9564]

@sanjay-kv Please assign this issue to me under GSSoC'24.

[Akanksha4554]

@sanjay-kv Please assign this issue to me under GSSoc'24.