conda env list
Hopefully you only see the "root" environment. Then type
source activate root
to get the mappings correct for your programs. Now type
python
and you should get the Anaconda version 3.X. Here is what I see
Python 3.6.1 |Anaconda 4.4.0 (x86_64)| (default, May 11 2017, 13:04:09) [GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>>
Now in the python console, type
import nltk nltk.download()
Use this GUI to find the "book" link in the "Collections" tab and download it. This will load many datasets and libraries.
Also install the VADER library and collection.
Next, exit out of python, back to the terminal. Time to install more libraries.
pip install afinn pip install graphviz pip install google-api-python-client pip install google-cloud-language
Finally, follow the Quickstart Instructions to get the credentials and libraries installed for Google Cloud. Because we are accessing the API through Python, you should not have to install the Cloud Tools.
conda env list
Hopefully you only see the "root" environment. Then type
activate root
to get the mappings correct for your programs. Now type
python
and you should get the Anaconda version 3.X. Here is what I see
Python 3.6.1 |Anaconda 4.4.0 (x86_64)| (default, May 11 2017, 13:04:09) [GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>>
Now in the python console, type
import nltk nltk.download()
Use this GUI to find the "book" link in the "Collections" tab and download it. This will load many datasets and libraries.
Also install the VADER library and collection.
Next, exit out of python, back to the terminal. Time to install more libraries.
pip install afinn pip install graphviz pip install google-api-python-client pip install google-cloud-language
Finally, follow the Quickstart Instructions to get the credentials and libraries installed for Google Cloud. Because we are accessing the API through Python, you should not have to install the Cloud Tools.
Use this tagger to find the part of speech for the bold words in the following sentences. How accurate are the taggings?
Use the Google Cloud API to parse these sentences and draw the resulting parse-tree using the graphvix library for Digraphs.
CHANGE FOR SENTENCE LENGTH
For the following sentence:
Gasper Hicks stared down at the dead teenager at the foot of his door and realized he knew him; knew him as a boy, from the days when Gasper taught Sunday school, knew him as a blonde, dirt-faced kid desperate for attention, knew him as one of the dozen anxious children they bussed from the trailer park.
compare the parse trees generated by the Stanford Parser and Google Cloud Natural Language. What differences in structure and/or tagging do you find? Do you think these differences are significant?