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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.
The labeled dataset consists of 50,000 IMDB movie reviews. No individual movie has more than 30 reviews. The 25,000 reviews labeled training set does not include any of the same movies as the 25,000 review test set.
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 dataset is comprised of 50,000 movie reviews from IMDb. This is a great starter dataset for Tensorflow.js and learning text classification/machine learning! This version of the dataset differs slightly from the source data.
We use the IMDB dataset with 50,000 polar movie reviews (positive or negative) Training data and test data: each 25,000 Training and testing sets are balanced (they contain an equal...
The IMDB Movie Review corpus is a standard dataset for the evaluation of text-classifiers. It consists of 25000 movies reviews from IMDB, labeled by sentiment (positive/negative). In this notebook a Convolutional Neural Network (CNN) is implemented for sentiment classification of IMDB reviews.
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.
