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2 months ago 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! 😊
Note: This repo is for beginners to learn and start with Opensource we won't accept more than 10 issues from a single person, This restriction applies to Gssoc project which has a similar kind of adding folder files, Points will be reduced when we find Spam.
I Maintain the repo issue twice a day, or ideally 1 day, If your issue goes stale for more than one day you can tag and comment on this same issue.
You can also check our CONTRIBUTING.md for guidelines on contributing to this project.
Taranpreet10451
sonali9564
Akanksha4554
Email Spam Classifier
This Python script utilizes machine learning techniques to classify emails as either spam or legitimate (ham). The classifier is built using logistic regression and employs the TF-IDF (Term Frequency-Inverse Document Frequency) vectorizer for feature extraction. Here's a brief overview of the workflow:
Data Preparation: The script loads email data from a CSV file and preprocesses it, handling missing values and converting categorical labels (spam, ham) to binary values.
Feature Extraction: TF-IDF vectorization is used to transform the text data into numerical features, capturing the importance of words in the documents.
Model Training: A logistic regression model is trained on the extracted features to learn patterns distinguishing between spam and ham emails.
Evaluation: The model's performance is evaluated on both training and testing datasets using accuracy metrics.
Prediction: Users can input an email message, and the model predicts whether it's spam or legitimate.
This classifier enables efficient identification of spam emails, contributing to a more organized and secure inbox experience.
Kindly assign it GSSoC label and mark it as a contribution under it