Sentipy
This package is a basic sentiment analyzer
About sentipy
Sentipy attempts to classify a text into positive, negative or neutral
sentiment. It uses Spacy's textcat with ensemble architecture in the back-end.
The ultimate objective of this package is to classify the sentiments as
accurately as possible
While the sentiment analysis at the core is absolutely basic, the current focus
is to understand the features the model is learning. sentipy leverages on
lime to get the features learnt and uses streamlit to crate a simple webapp
that helps with the visualization
How to install sentipy
- git clone the repo in to your local system
- run setup.py install
How to run the feature visualizer app
On your terminal run sentipy streamlit
What next?
- Use transformers and take the self supervised learning approach for classification
- Include visualizations for pre-processed text
- Make pre-processing options available on web app
- Better visualization