buntine

  # Clear existing task so we can replace it rather than "add" to it.
  Rake::Task["deploy:compile_assets"].clear 

  desc "Precompile assets locally and then rsync to web servers" 
  task :compile_assets do 
    on roles(:web) do 
      rsync_host = host.to_s 
 
      run_locally do 
        with rails_env: :production do ## Set your env accordingly.

Jesus

# Clear existing task so we can replace it rather than "add" to it.
Rake::Task["deploy:compile_assets"].clear 

desc "Precompile assets locally and then rsync to web servers" 
task :compile_assets do 
  # compile assets locally
  run_locally do
    with rails_env: fetch(:stage) do
      execute :bundle, "exec rake assets:precompile"
    end

gbuesing

UPDATE a fork of this gist has been used as a starting point for a community-maintained "awesome" list: machine-learning-with-ruby Please look here for the most up-to-date info!

Resources for Machine Learning in Ruby

Gems

• liblinear-ruby: Ruby interface to LIBLINEAR using SWIG

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

alvations

"""
Programming task
================

The following is an implementation of a simple Named Entity Recognition (NER).
NER is concerned with identifying place names, people names or other special
identifiers in text.

Here we make a very simple definition of a named entity: A sequence of
at least two consecutive capitalized words. E.g. "Los Angeles" is a named

jhilden

When using react-rails for an internationalized app it makes a lot of sense to use i18n-js for translations, so that you can reuse the the strings from your rails app's .yml files (and all the tooling & services that exist around that).

When you use the prerender feature of react-rails you face 2 problems:

• The first is that translation.js & i18n.js from i18n-js need to be loaded inside the server-side JS prerendering processes, which is achieved by loading them inside the components.js.
• The second problem is the server processes need to be aware of the current locale of each HTTP request. This is done by adding a custom renderer and using the before_render hook to configure i18n-js accordingly for each render call.

puf

'use strict';

var React = require('react-native');
var Firebase = require('firebase');
var {
  AppRegistry,
  StyleSheet,
  Text,
  View,
  TextInput,

benhoyt

"""Print most frequent N-grams in given file.

Usage: python ngrams.py filename

Problem description: Build a tool which receives a corpus of text,
analyses it and reports the top 10 most frequent bigrams, trigrams,
four-grams (i.e. most frequently occurring two, three and four word
consecutive combinations).

NOTES

kevin-smets

Requirements

Minikube requires that VT-x/AMD-v virtualization is enabled in BIOS. To check that this is enabled on OSX / macOS run:

sysctl -a | grep machdep.cpu.features | grep VMX

If there's output, you're good!

Prerequisites

zimuliu

module Concerns
  module NestedAttributesSync
    extend ActiveSupport::Concern

    included do
      class_attribute :nested_attributes_sync_options, instance_writer: false
      self.nested_attributes_sync_options = {}
    end

    class_methods do