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  1. 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.

  2. Large Movie Review Dataset.

    • Imdb_Reviews/Plain_Text
    • Imdb_Reviews/Bytes
    • Imdb_Reviews/Subwords8k
    • Imdb_Reviews/Subwords32k
    Config description: Plain text
    Dataset size: 129.83 MiB
    Feature structure:
    Config description: Uses byte-level text encoding withtfds.deprecated.text.ByteTextEncoder
    Dataset size: 129.88 MiB
    Feature structure:
    Config description: Uses tfds.deprecated.text.SubwordTextEncoderwith8k vocab size
    Dataset size: 54.72 MiB
    Feature structure:
    Config description: Uses tfds.deprecated.text.SubwordTextEncoderwith32k vocab size
    Dataset size: 50.33 MiB
    Feature structure:
  3. IMDb Dataset Details. Each dataset is contained in a gzipped, tab-separated-values (TSV) formatted file in the UTF-8 character set. The first line in each file contains headers that describe what is in each column. A ‘\N’ is used to denote that a particular field is missing or null for that title/name. The available datasets are as follows:

  4. imdb. like. 197. Tasks: Text Classification. Sub-tasks: sentiment-classification. Languages: English. Multilinguality: monolingual. Size Categories: 10K<n<100K. Language Creators: expert-generated. Annotations Creators: expert-generated. Source Datasets: original. Tags: Croissant. License: other. Dataset card Viewer Files Community. 6.

  5. Star 1. master. README. About Dataset IMDB dataset having 50K movie reviews for natural language processing or Text analytics. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing.

  6. Learn how to load, preprocess and decode the IMDB dataset of 25,000 movie reviews labeled by sentiment. The dataset is cached, indexed and truncated by default parameters.

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