Changes between Version 8 and Version 9 of private/NlpInPracticeCourse/TopicModelling

Timestamp:

Nov 10, 2020, 4:09:08 PM (3 years ago)

Author:

xrambous

Comment:

--

private/NlpInPracticeCourse/TopicModelling

@@ -17 +17 @@
 In this session we will use [[http://radimrehurek.com/gensim/|Gensim]] to model latent topics of Wikipedia documents. We will focus on Latent Semantic Analysis and Latent Dirichlet Allocation models.
 
+ 1. Gensim is already installed on epimetheus1.fi.muni.cz and it also offers faster model processing.
  1. Download and extract the corpus of Czech Wikipedia documents:  [[htdocs:bigdata/wiki.tar.bz2|wiki corpus]].
  1. Train LSA and LDA models of the corpus for various numbers of topics using Gensim. You can use this template: [raw-attachment:models.py models.py].
@@ -22 +23 @@
  1. Select 5 most important topics with 10 most important words, give them a name, save it into a text file and upload it into odevzdavarna.
 
-If you want faster model processing, login to epimetheus1.fi.muni.cz. You can save the files in your home directory on NLP computers and they will be accessible on the server.
+You can save the files in your home directory on NLP computers and they will be accessible on the server.