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email-filtering

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This tool allows you to clean a list of email addresses by removing unwanted domains and suffixes. It provides a user-friendly interface for specifying the domains and suffixes to keep. The cleaned email addresses are then saved to an output file.

  • Updated Nov 11, 2023

This tool designed to remove duplicate email addresses from a large email list file. Duplicate emails often clutter your mailing list and can lead to inefficiencies when sending emails. This tool helps you clean up your email list by eliminating duplicate entries.

  • Updated Nov 11, 2023

Automate your email workflow with this intelligent agent system. Features include email ingestion, filtering, summarization, action item extraction, and customizable notifications via various channels. Powered by LangChain, LangGraph, and Gemini 1.5 Flash.

  • Updated Jan 15, 2025
  • Jupyter Notebook

🇩📧️2️⃣️⌛️📖️ The official documentation source repository for the DMAIL implementation of the EMAIL 2 Sieve Filter specification, adding support for Sieve language filters to the DMAIL Email client.

  • Updated Jan 29, 2025
  • Markdown

The Email List Filtering Program is a C language program designed to validate and filter a list of email addresses. It ensures that each email address in the provided text file is valid and exists. The program helps to identify and remove fake or incorrect email addresses from the list, ensuring that the remaining email addresses are valid and reac

  • Updated Jul 11, 2023
  • C

🇩📧️2️⃣️⌛️💾️ The official source repository for the DMAIL implementation of the EMAIL 2 Sieve Filter specification, adding support for Sieve language filters to the DMAIL Email client.

  • Updated Jan 29, 2025
  • Sieve

SpamShield is a Flask-based web application that employs machine learning to swiftly identify and flag spam content in emails and text messages, offering users real-time protection against unwanted solicitations. With an intuitive interface and privacy-conscious design, SpamShield ensures efficient spam detection while safeguarding user privacy

  • Updated Jun 12, 2024
  • Jupyter Notebook

This project focuses on building a classifier to distinguish between spam and ham emails using Logistic Regression. Key steps include data preprocessing, feature extraction with TF-IDF vectorization, and model evaluation with accuracy metrics and a confusion matrix.

  • Updated Jul 13, 2024
  • Jupyter Notebook

Automate your email workflow with this intelligent agent system. Features include email ingestion, filtering, summarization, action item extraction, and customizable notifications via various channels. Powered by LangChain, LangGraph, and Gemini 1.5 Flash.

  • Updated Feb 1, 2025

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