When Machine Learning meets Food Delivery Startups: Ruby Sample Code | Hacker News Reader

When Machine Learning meets Food Delivery Startups: Ruby Sample Code

blog.prediction.io

37 pointssmhchan11 comments

So I just looked at the quick start demo code. Did everyone notice the irony in it? We created some fake people and some fake orders and randomly let the people see the fake orders. Then we try to predict based on this data. A bit silly isn't it?

But anyway, the whole thing seems pretty cool.

Best fake recommendations ever! But yeah we make the assumption the developer and their app (food delivery or otherwise) has some data (users, items, actions) on which to build a model. Otherwise you won't get very far...

Thanks! Some of our tutorials have test datasets (e.g., MovieLens) if you want to try it out - http://docs.prediction.io/current/tutorials/movie-recommenda...

I wish Seamless would innovate more. Recommended restaurants or meals would be awesome. Seamless has a total lock on the NYC market, but their website sucks, their ratings are highly unreliable (due to restaurants faking ratings), and they rarely add new features.

I wish Seamless would innovate more. is incompatible with Seamless has a total lock on the NYC market, sadly.

I wish you could search intra-menu. "Show me all restaurants with sweet potato fries within walking distance."

Yelp can kinda do that, and Google can kinda do that, but they are just going off reviews and not indexing menus attached to locations specifically.

This is actually a pretty good idea. Seamless does have a program that allows selected affiliates to get data dumps from them, you could probably build it based on that.

On second thought, I think you can already do that on their website, just not in their iOS app yet.

What I meant to wish for is discrete ordering. I want one sushi roll from place A, a dessert from place B, and chicken from place C (all collected and delivered by one person). That's more of a job for the exploitative labour task5rrrrrrrrr category though.

This is cool. I may try to do this (food ordering predictions) for my startup, with real data if I get some free time.

Is this entirely an open source project, or are there plans to do something like Keen.io?

Not so familiar with Keen IO. Looks like analytics-as-a-service for collecting and visualizing data. We're focused on helping developers build predictive features like recommendation, discovery, etc.

Yup. We're definitely committed to open source. Source is all up on GitHub https://github.com/predictionio

There is no data provided here. It's just a company blog saying how its product can be used.

Get a dabbawalla

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