Github allows me to call a JSON file like a server. So this is my raw data scrapped using apify (imdb-scrapper) 🇵🇸

The application will classify positively or negatively the review that is entered, you can use different models in total 4 that were used to preprocess and train with data from the IMBD dataset.

A unique sentiment analysis model on IMDB reviews with custom negation handling. Instead of generic preprocessing, it smartly tags words after negators like "not" (e.g., "not good" → "not_good"), preserving sentiment context. Comparison of models with and without this logic shows improved accuracy and real-world reliability.

Sentiment analysis on IMDB movie reviews using LSTM in TensorFlow

This is a Netflix clone built using ReactJS. It uses the TMDB API to fetch movies and display them. It also has a trailer feature which plays the trailer of the movie when clicked on the movie.

Implementation of the the research paper DPO: your language model is secretly a reward model