bsodhi
/ train_and_find_most_similar.py
Last active
July 6, 2019 08:11
Using gensim Doc2Vec for finding top N documents from pre-trained model which are most similar to a given out-of-training corpus.
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| """ Training a Doc2Vec model and finding top N documents from pre-trained model which are most similar to a given out-of-training corpus. | |
| Following sources have been the primary references for | |
| writing this module. | |
| * https://radimrehurek.com/gensim/models/doc2vec.html | |
| * https://github.com/RaRe-Technologies/gensim/blob/develop/docs/notebooks/doc2vec-lee.ipynb | |
| * https://radimrehurek.com/gensim/models/doc2vec.html#usage-examples | |
bsodhi
/ countries.json
Created
November 28, 2018 08:41
— forked from keeguon/countries.json
A list of countries in JSON
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| [ | |
| {name: 'Afghanistan', code: 'AF'}, | |
| {name: 'Åland Islands', code: 'AX'}, | |
| {name: 'Albania', code: 'AL'}, | |
| {name: 'Algeria', code: 'DZ'}, | |
| {name: 'American Samoa', code: 'AS'}, | |
| {name: 'AndorrA', code: 'AD'}, | |
| {name: 'Angola', code: 'AO'}, | |
| {name: 'Anguilla', code: 'AI'}, | |
| {name: 'Antarctica', code: 'AQ'}, |
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