Search Results for "spambayes"
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Showing 7 open source projects for "spambayes"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Bayes Anti-Spam
Anti Spam AddIn / Plugin for Outlook
For Outlook I had been using the SpamBayes plugin for years in order to remove spam e-mails. However, with Outlook 365 the addin stopped working for me. This reimplementation enables you to mark e-mails as spam or valid. Based on your input the addin learns how to classify e-mails. If the addin detects spam then it will move the e-mail to a configurable folder in Outlook. -
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*** NOTE: Version 4.0 development has moved to https://github.com/Hallikas/sspamm ... This space has saved as legacy data Semi's Spam Milter (sspamm), is python based SPAM filter for Sendmail that utilizes spambayes heurestic spam filtering. You also need Python Milter and Spambayes.
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Not all email clients have Spam filtering (and training) built in. Spam Trainer provides easy (drag and drop) training from your mail client, passing messages through to your spam filter (e.g. Spambayes) via command line scripts.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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This is a geek-oriented server-side spam filtering tool, running on Linux, based on spambayes and BerkelyDB, written mainly in python but with a little C. Goals of this project are: filtering precision, performance, customizability, code quality, fun ;)
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Quotient is multi-protocol (SMTP, POP, IMAP, SIP, HTTP, Q2Q) server that helps with all your online conversations be they over email, IRC, IM, mailing lists or voice over IP. It is written in Python on the Twisted framework and uses Lupy and SpamBayes.
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