Faculty Review using NLP

Inspiration

Faculty Review System uses Natural language processing for detecting the sentimentals of teachers can be used by education administrations to improve certain things in their organisation or it can be used for research purpose

What it does

The method of determining whether a piece of writing is positive, negative, or neutral is known as sentiment analysis. To assign weighted sentiment scores to entities, topics, themes, and categories inside a sentence or phrase, a sentiment analysis system for text analysis combines natural language processing (NLP) and machine learning techniques. Thus we have created the faculty review system which creates the graphs and analysis of sentiments like neutral, positive , negative and also produces graph such as pie charts and graphs for analysis .

How we built it

We built using Python , flask , html and css and deployed on heroku and also used the domain from godaddy registry where we have point the frontend and use CO:HERE api to buit model

Challenges we ran into

The hard part for us was integrating frontend with backend because we were doing this for first time working with flask and creating web application and interating CO:HERE

Accomplishments that we're proud of

At the end we have completed our project and we are proud of this thing despite of being at the different place and heavy schedule .

What we learned

We learn about the the Natural language Processing , flask , web-scraping , AI , ML and also about the teamwork ,and this was a first hackathon we have participate which can be kick start for our journey in hackathon and COHERE