I'm thinking about building a recommendation system in Ruby that accepts 8 attributes, the system will look at sample's matrix and then give recommendations based on the sample data. How do I do this? Thanks in advance
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I am trying to write a likelihood model in which the POI affects two samples, but while one I have the regular POI*yield, the other I have f(POI)*yield where f is an arbitrary function.
Is there a simple way to implement that in pyhf?
Thanks in advance.
pyhf currently does not support it, but it's something that is on our mind. Can you open an issue on our github with this as a feature request and we can work out how to do it.
I want to train RETURRN on LibriSpeech dataset using multiple GPUs, but don't know how to do.
Is this possible? I don't see any option to enable it in .config file.
Yes, it is possible. You find some description in the documentation. It currently uses Horovod, and basically you have to set use_horovod = True, but please see the documentation for further details.
I'm thinking of building an application that helps you find local businesses (just an example). You might enter your zip code (or GPS if this is on a phone) and find the closest business within 10 miles, etc. My question is how can I achieve this type of logic? Is there a library or service that I will need to use? Or can this be done with math? I'm not familiar with how this sort of thing usually works, so let me know how I need to store the records so I can query them later. Note: I will be using Ruby and MongoDB.
It should be easy to find the math to solve that, providing lat/long coordinates.
Or you could use some full featured gem to do that for you like Geocoder, that supports Mongoid or MongoMapper.
Next time you need some feature that might be a commun world problem, first check if there is a gem for that at ruby-toolbox, for this case here are some other gems for geocoding
One more solution here...
http://geokit.rubyforge.org/
I think, this topic is already discussed here..
I'm looking for a library or technique to detect the input language of blocks of text provided by users. Online lookups (like Google translate) won't work for this task as I'm writing an app which must run offline.
Thanks.
Here are two more n-gram-based gems you might want to try. They work offline.
https://github.com/echen/unsupervised-language-identification, optimized for separating english and other languages (has a live demo)
https://github.com/feedbackmine/language_detector, less specialized, will detect more languages. Some languages may need some extra training — I found it to be not precise enough for German text.
For anyone interested, I've found http://rubygems.org/gems/kenwaln-whatlanguage, which is performing excellently.
I'm using CLD which I really like, succinct and easy to use. Give it a try.
A quick demo of WhatLanguage in Ruby:
http://www.youtube.com/watch?v=lNqZ2cqOReo&list=UUJ_3fstMOH-g4yBxtvgAWkw&index=0&feature=plcp
I'd like to know what are the most recurrent in a given text or group of text (pulled from a database) in ruby.
Does anyone know what are the best practices?
You might start with statistical natural language processing. Also, you may be able to leverage one or more of the libraries mentioned on the AI Ruby Plugins page.