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I've thought about setting up a mail server on a DigitalOcean or Vultr VPS without any experience with mail servers (for person use). Whenever I read opinions about operating a private mail server, there's usually a few people that express great satisfaction in doing so, and say that it's not too difficult. However, there are also many more people that say it's not worth the effort since there's maintenance to consider, complex setup, and the cost of email providers is usually the same or less than running your own server.

What is your opinion (or others' if they'd like to chime in)? If you enjoy running your own, are there any guides in particular that you'd recommend? Does the future of email look even more prohibitively complex for self-hosting?


Editor's code completion based on deep learning.

a news aggregator that works. one where each person using it fills it with all sorts of metadata regarding why they liked/disliked a post/comment/embed etc, and then lets me use all the tagged metadata around content to sort it, possibly with some AI to help me.

slashdot seemed like it was on the right track, then the simplicity of the like/upvote threw complex out the window. buzzfeed came back with wtf/lol, but its not the same.


For anyone who is interested in efficiently classifying text, I can't recommend Vowpal Wabbit[1] (VW) enough. It's blazingly fast and has been used in both production and research. It also has a billion options out of the box for various different set-ups.

Other researchers have noted[2] that with a set of command line flags that vw is almost the same as the system described in the paper, specifically, "vw --ngrams 2 --log_multi [K] --nn 10".

Behind the speed of both methods is use of ngrams^, the feature hashing trick (think Bloom filter except for features) that has been the basis of VW since it began, hierarchical softmax (think finding an item in O(log n) using a balanced binary tree instead of an O(n) array traversal) and using a shallow instead of deep model.

I am still interested in the more detailed insights the team from Facebook AI Research may provide but the initial paper is a little light and they're still in the process of releasing the source code.

^ Illustrating ngrams: "the cat sat on the mat" => "the cat", "cat sat", "sat on", "on the", "the mat" - you lose complex positional and ordering information but for many text classification tasks that's fine.

[1]: https://github.com/JohnLangford/vowpal_wabbit/wiki

[2]: https://twitter.com/haldaume3/status/751208719145328640


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