Fundamentals of Deep Learning by Nikhil Buduma

Author:Nikhil Buduma
Language: eng
Format: epub, pdf
Publisher: O'Reilly Media, Inc.
Published: 2017-06-14T00:00:00+00:00

$ pip install gensim

We can subsequently load these vectors into memory using the following command:

from gensim.models import Word2Vec model = Word2Vec.load_word2vec_format('/path/to/googlenews.bin', binary=True)

The issue with this operation, however, is that it’s incredibly slow (it can take up to an hour, depending on the specs of your machine). To avoid loading the full dataset into memory every single time we run our program, especially while debugging code or experimenting with different hyperparameters, we cache the relevant subset of the vectors to disk using a lightweight database known as LevelDB.2 To build the appropriate Python bindings (which allow us to interact with a LevelDB instance from Python), we simply use the following command:

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