Changes between Version 36 and Version 37 of private/NlpInPracticeCourse/OpinionSentiment

Timestamp:

Oct 8, 2020, 10:17:06 AM (4 years ago)

Author:

Ales Horak

Comment:

--

private/NlpInPracticeCourse/OpinionSentiment

@@ -24 +24 @@
 === Technical Requirements === 
 
+The task will proceed using Python notebook run in web browser in the [https://colab.research.google.com/ Google Colaboratory] environment 
+with the MU G-Suite disk access.
+
+In case of running the codes in a local environment, the requirements are 
+Python 3, jupyter notebook, modules NLTK, scipy, numpy, pandas, and sklearn.
 
 
@@ -31 +36 @@
 We use the Liu's Opinion Lexion. For Czech SA, we use the automatically translated version. Next, we try to compensate drawbacks of the lexicon by computing word vectors in a simple way.
 
-Requirements: Google Colab environment: https://colab.research.google.com/drive/1j9f28cnFrcRmWKhylP6kXhMwtksnhyCo?usp=sharing
+Access the [https://colab.research.google.com/drive/1j9f28cnFrcRmWKhylP6kXhMwtksnhyCo Python notebook in the Google Colab environment]. Do not forget to save your work if you want to see your changes later, leaving the browser will throw away all changes!
 
 OR
 
-(local version) Python 3, jupyter notebook, modules NLTK, scipy, numpy, pandas, sklearn
+(local version) 
 
-In case of Google Colab don't forget to save your work if you want to see your changes later!
 
-Files: [raw-attachment:cestina20.csv cestina20.csv], [raw-attachment:cestina20_annotation.csv cestina20_annotation.csv],
-[raw-attachment:urban_dictionary.csv urban_dictionary.csv]
- [raw-attachment:Word_Vectors_and_Sentiment.ipynb Word_Vectors_and_Sentiment.ipynb], [raw-attachment:negative-words-en.txt negative-words-en.txt], [raw-attachment:negative-words-cs.txt negative-words-cs.txt], [raw-attachment:positive-words-en.txt positive-words-en.txt], [raw-attachment:positive-words-cs.txt positive-words-cs.txt]
+Files: [raw-attachment:Word_Vectors_and_Sentiment.ipynb Word_Vectors_and_Sentiment.ipynb], [raw-attachment:cestina20.csv cestina20.csv], [raw-attachment:cestina20_annotation.csv cestina20_annotation.csv],
+[raw-attachment:urban_dictionary.csv urban_dictionary.csv], [raw-attachment:negative-words-en.txt negative-words-en.txt], [raw-attachment:negative-words-cs.txt negative-words-cs.txt], [raw-attachment:positive-words-en.txt positive-words-en.txt], [raw-attachment:positive-words-cs.txt positive-words-cs.txt]
 
 1. Create `<YOUR_FILE>`, a text file named ia161-UCO-01.txt where UCO is your university ID.