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mindshare in this community, too (though it already has plenty of that thanks to Tensorflow
and other projects). Kaggle has a bit of a history with Google, too, but that's pretty recent.
Earlier this month, Google and Kaggle teamed up to host a $100,000 machine learning competition
around classifying YouTube videos. That competition had some deep integrations with the
Google Cloud Platform, too. Our understanding is that Google will keep the service running -
likely under its current name. While the acquisition is probably more about Kaggle's community
than technology, Kaggle did build some interesting tools for hosting its competition and 'kernels',
too. On Kaggle, kernels are basically the source code for analyzing data sets and developers can
share this code on the platform (the company previously called them 'scripts'). Like similar
competition-centric sites, Kaggle also runs a job board, too. It's unclear what Google will do
with that part of the service. According to Crunchbase, Kaggle raised $12.5 million (though PitchBook
says it's $12.75) since its launch in 2010. Investors in Kaggle include Index Ventures, SV Angel,
Max Levchin, Naval Ravikant, Google chief economist Hal Varian, Khosla Ventures and Yuri Milner
"""
pyake = yake.KeywordExtractor(lan="en",n=3)
result = pyake.extract_keywords(text_content)
print(result)
keywords = [kw[0] for kw in result]
print(keywords)
assert "google" in keywords
assert "kaggle" in keywords
assert "san francisco" in keywords
assert "machine learning" in keywords
def run_yake(text_content):
myake = yake.KeywordExtractor(lan=language, n=ngram_size, dedupLim=dedup_lim, dedupFunc=dedup_func,
windowsSize=window_size, top=top)
results = myake.extract_keywords(text_content)
table = []
for kw in results:
if (verbose):
table.append({"keyword":kw[0], "score":kw[1]})
else:
table.append({"keyword":kw[0]})
print(tabulate(table, headers="keys"))
score:
type: number
"""
try:
assert request.json["text"] , "Invalid text"
assert len(request.json["language"]) == 2, "Invalid language code"
assert int(request.json["max_ngram_size"]) , "Invalid max_ngram_size"
assert int(request.json["number_of_keywords"]) , "Invalid number_of_keywords"
text = request.json["text"]
language = request.json["language"]
max_ngram_size = int(request.json["max_ngram_size"])
number_of_keywords = int(request.json["number_of_keywords"])
my_yake = yake.KeywordExtractor(lan=language,
n=max_ngram_size,
top=number_of_keywords,
dedupLim=0.8,
windowsSize=2
)
keywords = my_yake.extract_keywords(text)
result = [{"ngram":x[1] ,"score":x[0]} for x in keywords]
return jsonify(result), HTTPStatus.OK
except IOError as e:
return jsonify("Language not supported"), HTTPStatus.BAD_REQUEST
except Exception as e:
return jsonify(str(e)), HTTPStatus.BAD_REQUEST