The dataset comprises 25,000 movie reviews from IMDB, labeled by sentiment (positive/negative). Reviews have been preprocessed, and each review is encoded as a sequence of word indices (integers). The ...

This project provides a comprehensive analysis of the IMDb movie dataset. The primary goal is to extract meaningful insights and trends from the movie industry through a multi-stage process: ...

Abstract: Sentiment analysis plays a critical role in natural language processing as it seeks to identify and categorize the emotions expressed in texts. In this study, we conducted a case analysis ...

This demo from Dr. James McCaffrey of Microsoft Research of creating a prediction system for IMDB data using an LSTM network can be a guide to create a classification system for most types of text ...

The goal of the IMDB dataset problem is to predict if a movie review has positive sentiment ("I liked this movie") or negative sentiment ("The film was a disappointment"). This article explains how to ...