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consumer_key = 'your-consumer-key'
consumer_secret = 'your-consumer-secret'
access_token = 'your-access-token'
access_secret = 'your-access-secret'

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smartinsightsfromdata

use gdal to covert coordinate system

ogr2ogr -t_srs EPSG:4326 CCG_APR_2013_EN_BFE_WGS84.shp CCG_APR_2013_EN_BFE.shp

use topojson to simply & convert format

hires:

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import json
import urlparse
from itertools import chain
flatten = chain.from_iterable

from nltk import word_tokenize

from gensim.corpora import Dictionary
from gensim.models.ldamodel import LdaModel
from gensim.models.tfidfmodel import TfidfModel

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"""
preprocess-twitter.py

python preprocess-twitter.py "Some random text with #hashtags, @mentions and http://t.co/kdjfkdjf (links). :)"

Script for preprocessing tweets by Romain Paulus
with small modifications by Jeffrey Pennington
with translation to Python by Motoki Wu

Translation of Ruby script to create features for GloVe vectors for Twitter data.

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import sys
import logging
import numpy
import gensim


logging.basicConfig(level=logging.INFO)

train_sentences = gensim.models.doc2vec.LabeledLineSentence(sys.argv[1])
model = gensim.models.Doc2Vec(train_sentences, size=400, window=8, min_count=2,

smartinsightsfromdata

Whiplash for cash fraud detection

This interactive Neo4j graph tutorial presents how whiplash for cash, a popular insurance fraud, can be identified with the help of Neo4j. All the ideas come from the great presentation of Gorka Sadowski and Philip Rathle.

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Carousel fraud detection

This interactive Neo4j graph tutorial shows how to detect a popular fraud scam called "carousel fraud". It is written by Scott Mongeau (Data Scientist @ SARK7) and Jean Villedieu (Co-Founder of Linkurious). Recently a £1 billion VAT fraud connected to terrorism was discovered.

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smartinsightsfromdata

Reshipping scam detection.adoc

This interactive Neo4j graph tutorial shows how ecommerce websites can use their data to identify reshipping scams.

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