project-sean

Inspiration

Emotions are an essential part of our lives, and they can make a huge difference in the way we interact with machines. By bringing emotions into the world of AI, we can create more meaningful and personalized experiences for users. Whether it's in healthcare, education, or customer service, the ability of machines to understand and respond to our emotions can make a real difference in our lives. Emotion recognition and sentiment analysis are just some of the ways we can create more empathetic and human-like interactions between humans and machines.

What it does

By using React and Sass for the front end, and Django for the back end, a web application is built that allows users to interact with the sentiment analysis model trained on the IMDB dataset. The application can take in user comments and classify them as positive or negative in real time, providing a user-friendly way to perform sentiment analysis on large volumes of text data.

How we built it

Here are the steps:-

First we searched for a dataset.
We preprocessed the data and divided it into test and training datasets
Created a model based on the datasets.
Integrated model with backend
Integrated backend with frontend

Challenges we ran into

The first and foremost challenge was to create a model for the same. We did so using the TensorFlow model which was In python so we ran into problems while integrating it with the front end. For that, since we used javascript it was a bit challenging to integrate. Also, we ran into Cross Origin errors which are common if haven't whitelisted the front end.