
Show HN: Tamber – put real time, high-accuracy recommendations in your app - alexirobbins
https://tamber.com
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alexirobbins
Hi all! I'm Alexi, founder of Tamber. We built Tamber to help developers put
fast, effective recommendations into their apps.

After trying a few open source libraries for a music app I was building, I
found that they were surprisingly tedious to implement and tended to overfit
for popular items – Neil Young _is_ similar to Bob Dylan, but that doesn't
help you discover new music. I knew there had to be a better approach that
would solve this popularity bias problem, and make recommendations less
painful to implement.

Tamber overcomes popularity bias by learning not only the relationships
between items, but also how trends in taste evolve over time and using that
information to boost less-well-known items in recommendations.

It works just like an analytics service, except that every event you track
triggers a system-wide update to the model. And it's really fast, returning
fresh suggestions in 20-120ms. So as a user navigates around your app (even if
they aren't signed in!) your app can always display the optimal set of next
things they should see next.

Here is a simple demo app for book recommendations we made using Goodreads
data pulled from Kaggle:
[https://tamber.com/demo/goodbooks](https://tamber.com/demo/goodbooks)

I'll open source the app code once I clean it up a bit.

Looking forward to hearing your thoughts and feedback!

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LoremTech
Our company has been using this for a few months now and it’s seriously
awesome - has saved our developers about 100 hours of work...paid for itself
10X over and seeing a bump in user time in product

