ReCo
Hint to Your Clients What They Want to Buy or See in a Precise and Friendly Way
Scalable, cloud-based recommendation platform built on top of cutting edge machine learning algorithms.
Know Your Clients
No matter how wide the range of products you’re selling, our machine learning algorithms will discover your clients’ latent preferences and the hidden product features using your big (or not that big) data.
Developer Friendly
[product name] is language-agnostic. Upload existing or real-time data using the language your application is written in and request recommendations for a user with the REST API.
ReCo is growing fast. Want to see just how much? Sign up and we'll let you know
Examine the Quality of Recommendations
If you already have a dataset with your clients’ preferences you can run the [product name] on it to see if the quality of recommendations is good enough for you. Want to try? Then, please, contact us.
Do One Thing but Do It Well
We don’t spam your clients with emails. We don’t force you to throw your existing solutions away. What we do is we learn from data and deliver recommendations. Period.
>>> from reco import Reco
>>> reco = Reco(token='ade631d30ba0e1be531c4fbc98c60053ee5f3853')
>>> reco.send(user_id=123, item_id=321, score=5)
>>> reco.get_recommendations(user_id=312, count=10)
[Recommendation(user_id=312, item_id=21352, weight=4.9), ...]
>>> reco.recommend_user_for(item_id=311, count=10)
[Recommendation(user_id=312, item_id=21352, weight=4.9), ...]
>>> reco.get_top(count=100)
[Item(id=321, score=4.97, count=27521),
Item(id=321, score=4.77, count=22125),
...]
>>> reco.tranding().week()
[Item(id=46295, count=3136), Item(id=89870, count=2559)]import { Reco } from 'reco'
const reco = Reco(token='ade631d30ba0e1be531c4fbc98c60053ee5f3853')
reco.send(userID=123, itemID=321, score=5)
reco.getRecommendations(userID=312, count=10)
reco.recommendUserFor(itemID=311, count=10)
reco.getTop(count=100)
reco.tranding().week()$ http POST api.reco.com/ratings/ Token:ade631d30ba0e1be531c4fbc98c60053ee5f3853 user_id=123 item_id=321 score=5
$ http GET api.reco.com/recommendations/user/123/ Token:ade631d30ba0e1be531c4fbc98c60053ee5f3853 count=10
$ http GET api.reco.com/recommendations/item/123/ Token:ade631d30ba0e1be531c4fbc98c60053ee5f3853 count=10
$ http GET api.reco.com/top/ Token:ade631d30ba0e1be531c4fbc98c60053ee5f3853 count=100
$ http GET api.reco.com/tranding/week/ Token:ade631d30ba0e1be531c4fbc98c60053ee5f3853 count=100