Re: UR PredictionIO quickstart

The first thing you’ll run into is storage in-memory for all user and item ids. 20,000 products that have sold and 42,500 users who have bought. This might fit in a 16g memory machine but also might require 32g. The number of sales is not a big factor. You may even be able to connect it to your

Re: UR PredictionIO quickstart

65000 orders. 100.000 items. Not many items per order. 80.000 products. Only 20.000 are sold at least once. 85.000 customers. Half of the customers have bought at least one product according to this trainingsdata. 1500 categories. 150 manufactures. Currently a maximum of 5 properties for

Re: UR PredictionIO quickstart

Probably, how many users and items? It will certainly work on a single machine, you may have to pick a less than minimal instance type. We recommend R3 instances and you can upgrade in place if you start out too small. On May 10, 2017, at 10:45 AM, Dennis Honders

Re: UR PredictionIO quickstart

Okay, thanks for the answer. Will also take a look at the update next week. In my case I have like 65000 orders and the complete dataset is about 700.000 records. For confirmation, this is considered a small dataset, and small enough for experimenting (Not using it in production) with the UR?

Re: UR PredictionIO quickstart

Yes unless you have large-ish data. We also have and AWS AMI all set up here: http://actionml.com/docs/awssetupguide . Both should be fine for experimentation but will be too small for big-data. BTW all are being updated to the UR V0.6.0 and PIO 0.11.0