Show HN: The Sample – newsletters curated for you with machine learning

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

Our great sponsors
  • Scout APM - Less time debugging, more time building
  • SonarLint - Deliver Cleaner and Safer Code - Right in Your IDE of Choice!
  • SaaSHub - Software Alternatives and Reviews
  • Surprise

    A Python scikit for building and analyzing recommender systems

    I'm planning to build a business on this, so probably won't open-source it--but I'm always looking for interesting things to write about! I write a weekly newsletter called Future of Discovery[1]; I might write up some more implementation details there in a week or two. In the mean time, most of the heavy lifting is done by the Surprise python lib[2]. It's pretty easy to play around with, just give it a csv of , , and then you can start making rating predictions. Also fastText[3] is easy to mess around with too. Most of the code I've written just layers things on top of that, e.g. to handle exploration-vs-exploitation as discussed in another thread here.

    Recently I've been factoring out the ML code into a separate recommendation service so it can different kinds of apps (I just barely made this essay recommender system[4] start using it for example).

    I'm happy to chat about recommender systems also if you like, email's in my profile.

    [1] https://findka.com

    [2] http://surpriselib.com/

    [3] https://fasttext.cc/

    [4] https://essays.findka.com

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts