| Line 6: | Line 6: | ||
Made by Google, uses Neural Net, performs good on semantics. | Made by Google, uses Neural Net, performs good on semantics. | ||
=== Installation + getting started: === | === Installation + getting started: === | ||
| − | <code>pip install gensim</code> | + | <code>pip install gensim</code><br> |
| − | Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python] | + | 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/]. | ||
==Fastword== | ==Fastword== | ||
For a general explanation look here: [1]
Made by Google, uses Neural Net, performs good on semantics.
pip install gensim
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 Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---> apparently) see here: [4] Pretrained model files are HUGE