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selected_words = [
    'receipt', 
    'card', 
    'refund', 
    'month',
    'monthly',
    'plan', 
    'profit', 
    'charged',
    'charge',

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# Example Dockerfile
FROM hello-world

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To install scikit-learn easily run the following command.

curl https://gist.githubusercontent.com/dacamo76/4780765/raw/c3779996d8f6b13caaaa48d33aa1585684c7f8e6/scikit-learn-install.sh | sh

Please look over the shell file being run to make sure no evil is done to your machine.

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Resources for Machine Learning in Ruby

Gems

• liblinear-ruby: Ruby interface to LIBLINEAR using SWIG

• classifier-reborn: Bayesian and LSI classification
  dependencies: GSL

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#System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

##Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

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### Hash implementation in python
def custom_hash(key):
    """
    Return the hash value of the given key. Uses dbj2

    @param key: String or unicode
    """
    result = 5381
    multiplier = 33

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# Code example for:
# Hello World - Machine Learning Recipes #1 - Google Developers
# https://www.youtube.com/watch?v=cKxRvEZd3Mw

from sklearn import tree

# Bumpy = 0, Smooth = 1
features = [[140, 1], [130, 1], [150, 0], [170, 0]]
# Apple = 0, Orange = 1
labels = [0, 0, 1, 1]

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# Simple:
# a --> b
#   --> c --> d
#   --> d 
graph1 = {
    "a": ["b", "c", "d"],
    "b": [],
    "c": ["d"],
    "d": []
}