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This project aims to perform sentiment analysis on the IMDB movie review dataset. It utilizes deep learning techniques, particularly LSTM and Conv1D layers, to classify movie reviews into positive and negative sentiments. The model is built using Keras and GloVe embeddings for word representations.
Internet Movie Database users are invited to participate in the site's ever-growing wealth of information by rating movies on a rating scale. The labeled dataset consists of 50,000 IMDB movie reviews. No individual movie has more than 30 reviews.
IMDB Movie Reviews Large Dataset - 50k Reviews. This dataset is taken from https://ai.stanford.edu/~amaas/data/sentiment/ and then preprocess to put all positive and negative reviews in the same file for training and testing.
In this project, I will use IMDB movie reviews. This dataset contains 50,000 movie's reviews from IMDB, labeled by sentiment (positive/negative). The dataset can be loaded and splitted into training and test sets as the following.
The IMDb Movie Reviews dataset is a binary sentiment analysis dataset consisting of 50,000 reviews from the Internet Movie Database (IMDb) labeled as positive or negative. The dataset contains an even number of positive and negative reviews. Only highly polarizing reviews are considered.
The IMDb Movie Reviews dataset is a binary sentiment analysis dataset consisting of 50,000 reviews from the Internet Movie Database (IMDb) labeled as positive or negative. The dataset contains an even number of positive and negative reviews. Only highly polarizing reviews are considered.
1 kwi 2021 · Reviews. Concrete Cowboy. 111 minutes ‧ R ‧ 2021. Odie Henderson. April 1, 2021. 5 min read. If you know your history, the concept of a Black cowboy will not seem foreign. They’re part of a rich American story that spans centuries and seldom goes explored in cinema or in reality.
