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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Loft Tokyo? ASK AN EXPERT?
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
ASK AN EXPERT @ AWS Loft Tokyo !
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Cloud9
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Analyzing ASK AN EXPERT Logs !
Tokenization Word2Vec
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Analyzing ASK AN EXPERT Logs !
Tokenization
from janome.tokenizer import Tokenizer
t = Tokenizer("userdic.csv", udic_enc="utf8")
f = io.open('./sodan.txt', 'r', encoding='utf-8’)
tokens = t.tokenize(line)
for token in tokens:
partOfSpeech = token.part_of_speech.split(',')[0]
if partOfSpeech == u'’:
if token.surface == ‘https’: pass
elif token.surface.isnumeric(): pass
else: sodan_words.append(token.surface)
https://github.com/mocobeta/janome
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Analyzing ASK AN EXPERT Logs !
Word2Vec
from gensim.models import word2vec
sodan_sentences = word2vec.Text8Corpus('./sodan_words.txt')
sodan_model = word2vec.Word2Vec(sodan_sentences, size=200,
min_count=20, window=15)
results = sodan_model.wv.most_similar(positive=[u''])
for result in results:
print(result)
https://github.com/RaRe-Technologies/gensim
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
ASK AN EXPERT Logs !
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© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Loft Tokyo - ASK AN EXPERT Logs
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