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=== Installation + getting started: === | === Installation + getting started: === | ||
+ | Included in the ''gensim'' package. | ||
+ | |||
+ | To install, just type | ||
+ | |||
<code>pip install gensim</code><br> | <code>pip install gensim</code><br> | ||
+ | |||
+ | into a command window. | ||
+ | |||
Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]<br> | Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]<br> | ||
Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/]. | Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/]. | ||
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=== Installation + getting started: === | === Installation + getting started: === | ||
− | Included in | + | Included in the ''gensim'' package. |
+ | |||
+ | To install, just type | ||
+ | |||
+ | <code>pip install gensim</code><br> | ||
+ | |||
+ | into a command window. | ||
+ | |||
Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html] | Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html] | ||
For a general explanation look here: [1]
Made by Google, uses Neural Net, performs good on semantics.
Included in the gensim package.
To install, just type
pip install gensim
into a command window.
Here are some of the things you can do with the model: [2]
Here is a bit of background information an an explanation how to train your own models: [3].
Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---> apparently) see here:
[4]
Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory
Included in the gensim package.
To install, just type
pip install gensim
into a command window.
Documentation is here: [5]
Invented by the Natural language processing group in standford. [6]Uses more conventional math instead of Neural Network "Black Magic". Seems to perform very slightly less well than Word2vec and FastWord.