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amazon_us_reviews

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns : marketplace - 2 letter country code of the marketplace where the review was written. customer_id - Random identifier that can be used to aggregate reviews written by a single author. review_id - The unique ID of the review. product_id - The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id. product_parent - Random identifier that can be used to aggregate reviews for the same product. product_title - Title of the product. product_category - Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). star_rating - The 1-5 star rating of the review. helpful_votes - Number of helpful votes. total_votes - Number of total votes the review received. vine - Review was written as part of the Vine program. verified_purchase - The review is on a verified purchase. review_headline - The title of the review. review_body - The review text. review_date - The date the review was written.

amazon_us_reviews is configured with tfds.structured.amazon_us_reviews.AmazonUSReviewsConfig and has the following configurations predefined (defaults to the first one):

  • Wireless_v1_00 (v0.1.0) (Size: 1.59 GiB): A dataset consisting of reviews of Amazon Wireless_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Watches_v1_00 (v0.1.0) (Size: 155.42 MiB): A dataset consisting of reviews of Amazon Watches_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Video_Games_v1_00 (v0.1.0) (Size: 453.19 MiB): A dataset consisting of reviews of Amazon Video_Games_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Video_DVD_v1_00 (v0.1.0) (Size: 1.41 GiB): A dataset consisting of reviews of Amazon Video_DVD_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Video_v1_00 (v0.1.0) (Size: 132.49 MiB): A dataset consisting of reviews of Amazon Video_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Toys_v1_00 (v0.1.0) (Size: 799.61 MiB): A dataset consisting of reviews of Amazon Toys_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Tools_v1_00 (v0.1.0) (Size: 318.32 MiB): A dataset consisting of reviews of Amazon Tools_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Sports_v1_00 (v0.1.0) (Size: 832.06 MiB): A dataset consisting of reviews of Amazon Sports_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Software_v1_00 (v0.1.0) (Size: 89.66 MiB): A dataset consisting of reviews of Amazon Software_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Shoes_v1_00 (v0.1.0) (Size: 612.50 MiB): A dataset consisting of reviews of Amazon Shoes_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Pet_Products_v1_00 (v0.1.0) (Size: 491.92 MiB): A dataset consisting of reviews of Amazon Pet_Products_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Personal_Care_Appliances_v1_00 (v0.1.0) (Size: 16.82 MiB): A dataset consisting of reviews of Amazon Personal_Care_Appliances_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • PC_v1_00 (v0.1.0) (Size: 1.41 GiB): A dataset consisting of reviews of Amazon PC_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Outdoors_v1_00 (v0.1.0) (Size: 428.16 MiB): A dataset consisting of reviews of Amazon Outdoors_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Office_Products_v1_00 (v0.1.0) (Size: 488.59 MiB): A dataset consisting of reviews of Amazon Office_Products_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Musical_Instruments_v1_00 (v0.1.0) (Size: 184.43 MiB): A dataset consisting of reviews of Amazon Musical_Instruments_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Music_v1_00 (v0.1.0) (Size: 1.42 GiB): A dataset consisting of reviews of Amazon Music_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Mobile_Electronics_v1_00 (v0.1.0) (Size: 21.81 MiB): A dataset consisting of reviews of Amazon Mobile_Electronics_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Mobile_Apps_v1_00 (v0.1.0) (Size: 532.11 MiB): A dataset consisting of reviews of Amazon Mobile_Apps_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Major_Appliances_v1_00 (v0.1.0) (Size: 23.23 MiB): A dataset consisting of reviews of Amazon Major_Appliances_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Luggage_v1_00 (v0.1.0) (Size: 57.53 MiB): A dataset consisting of reviews of Amazon Luggage_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Lawn_and_Garden_v1_00 (v0.1.0) (Size: 464.22 MiB): A dataset consisting of reviews of Amazon Lawn_and_Garden_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Kitchen_v1_00 (v0.1.0) (Size: 887.63 MiB): A dataset consisting of reviews of Amazon Kitchen_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Jewelry_v1_00 (v0.1.0) (Size: 235.58 MiB): A dataset consisting of reviews of Amazon Jewelry_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Home_Improvement_v1_00 (v0.1.0) (Size: 480.02 MiB): A dataset consisting of reviews of Amazon Home_Improvement_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Home_Entertainment_v1_00 (v0.1.0) (Size: 184.22 MiB): A dataset consisting of reviews of Amazon Home_Entertainment_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Home_v1_00 (v0.1.0) (Size: 1.01 GiB): A dataset consisting of reviews of Amazon Home_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Health_Personal_Care_v1_00 (v0.1.0) (Size: 964.34 MiB): A dataset consisting of reviews of Amazon Health_Personal_Care_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Grocery_v1_00 (v0.1.0) (Size: 382.74 MiB): A dataset consisting of reviews of Amazon Grocery_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Gift_Card_v1_00 (v0.1.0) (Size: 11.57 MiB): A dataset consisting of reviews of Amazon Gift_Card_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Furniture_v1_00 (v0.1.0) (Size: 142.08 MiB): A dataset consisting of reviews of Amazon Furniture_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Electronics_v1_00 (v0.1.0) (Size: 666.45 MiB): A dataset consisting of reviews of Amazon Electronics_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Video_Games_v1_00 (v0.1.0) (Size: 26.17 MiB): A dataset consisting of reviews of Amazon Digital_Video_Games_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Video_Download_v1_00 (v0.1.0) (Size: 483.49 MiB): A dataset consisting of reviews of Amazon Digital_Video_Download_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Software_v1_00 (v0.1.0) (Size: 18.12 MiB): A dataset consisting of reviews of Amazon Digital_Software_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Music_Purchase_v1_00 (v0.1.0) (Size: 241.82 MiB): A dataset consisting of reviews of Amazon Digital_Music_Purchase_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Ebook_Purchase_v1_00 (v0.1.0) (Size: 2.51 GiB): A dataset consisting of reviews of Amazon Digital_Ebook_Purchase_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Camera_v1_00 (v0.1.0) (Size: 422.15 MiB): A dataset consisting of reviews of Amazon Camera_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Books_v1_00 (v0.1.0) (Size: 2.55 GiB): A dataset consisting of reviews of Amazon Books_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Beauty_v1_00 (v0.1.0) (Size: 871.73 MiB): A dataset consisting of reviews of Amazon Beauty_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Baby_v1_00 (v0.1.0) (Size: 340.84 MiB): A dataset consisting of reviews of Amazon Baby_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Automotive_v1_00 (v0.1.0) (Size: 555.18 MiB): A dataset consisting of reviews of Amazon Automotive_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Apparel_v1_00 (v0.1.0) (Size: 618.59 MiB): A dataset consisting of reviews of Amazon Apparel_v1_00 products in US marketplace. Each product has its own version as specified with it.

  • Digital_Ebook_Purchase_v1_01 (v0.1.0) (Size: 1.21 GiB): A dataset consisting of reviews of Amazon Digital_Ebook_Purchase_v1_01 products in US marketplace. Each product has its own version as specified with it.

  • Books_v1_01 (v0.1.0) (Size: 2.51 GiB): A dataset consisting of reviews of Amazon Books_v1_01 products in US marketplace. Each product has its own version as specified with it.

  • Books_v1_02 (v0.1.0) (Size: 1.24 GiB): A dataset consisting of reviews of Amazon Books_v1_02 products in US marketplace. Each product has its own version as specified with it.

amazon_us_reviews/Wireless_v1_00

A dataset consisting of reviews of Amazon Wireless_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 9,002,021
TRAIN 9,002,021

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Watches_v1_00

A dataset consisting of reviews of Amazon Watches_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 960,872
TRAIN 960,872

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Video_Games_v1_00

A dataset consisting of reviews of Amazon Video_Games_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,785,997
TRAIN 1,785,997

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Video_DVD_v1_00

A dataset consisting of reviews of Amazon Video_DVD_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,069,140
TRAIN 5,069,140

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Video_v1_00

A dataset consisting of reviews of Amazon Video_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 380,604
TRAIN 380,604

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Toys_v1_00

A dataset consisting of reviews of Amazon Toys_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,864,249
TRAIN 4,864,249

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Tools_v1_00

A dataset consisting of reviews of Amazon Tools_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,741,100
TRAIN 1,741,100

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Sports_v1_00

A dataset consisting of reviews of Amazon Sports_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,850,360
TRAIN 4,850,360

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Software_v1_00

A dataset consisting of reviews of Amazon Software_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 341,931
TRAIN 341,931

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Shoes_v1_00

A dataset consisting of reviews of Amazon Shoes_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,366,916
TRAIN 4,366,916

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Pet_Products_v1_00

A dataset consisting of reviews of Amazon Pet_Products_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,643,619
TRAIN 2,643,619

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Personal_Care_Appliances_v1_00

A dataset consisting of reviews of Amazon Personal_Care_Appliances_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 85,981
TRAIN 85,981

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/PC_v1_00

A dataset consisting of reviews of Amazon PC_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 6,908,554
TRAIN 6,908,554

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Outdoors_v1_00

A dataset consisting of reviews of Amazon Outdoors_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,302,401
TRAIN 2,302,401

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Office_Products_v1_00

A dataset consisting of reviews of Amazon Office_Products_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,642,434
TRAIN 2,642,434

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Musical_Instruments_v1_00

A dataset consisting of reviews of Amazon Musical_Instruments_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 904,765
TRAIN 904,765

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Music_v1_00

A dataset consisting of reviews of Amazon Music_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,751,577
TRAIN 4,751,577

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Mobile_Electronics_v1_00

A dataset consisting of reviews of Amazon Mobile_Electronics_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 104,975
TRAIN 104,975

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Mobile_Apps_v1_00

A dataset consisting of reviews of Amazon Mobile_Apps_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,033,376
TRAIN 5,033,376

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Major_Appliances_v1_00

A dataset consisting of reviews of Amazon Major_Appliances_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 96,901
TRAIN 96,901

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Luggage_v1_00

A dataset consisting of reviews of Amazon Luggage_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 348,657
TRAIN 348,657

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Lawn_and_Garden_v1_00

A dataset consisting of reviews of Amazon Lawn_and_Garden_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,557,288
TRAIN 2,557,288

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Kitchen_v1_00

A dataset consisting of reviews of Amazon Kitchen_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,880,466
TRAIN 4,880,466

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Jewelry_v1_00

A dataset consisting of reviews of Amazon Jewelry_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,767,753
TRAIN 1,767,753

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Home_Improvement_v1_00

A dataset consisting of reviews of Amazon Home_Improvement_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,634,781
TRAIN 2,634,781

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Home_Entertainment_v1_00

A dataset consisting of reviews of Amazon Home_Entertainment_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 705,889
TRAIN 705,889

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Home_v1_00

A dataset consisting of reviews of Amazon Home_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 6,221,559
TRAIN 6,221,559

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Health_Personal_Care_v1_00

A dataset consisting of reviews of Amazon Health_Personal_Care_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,331,449
TRAIN 5,331,449

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Grocery_v1_00

A dataset consisting of reviews of Amazon Grocery_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 2,402,458
TRAIN 2,402,458

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Gift_Card_v1_00

A dataset consisting of reviews of Amazon Gift_Card_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 149,086
TRAIN 149,086

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Furniture_v1_00

A dataset consisting of reviews of Amazon Furniture_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 792,113
TRAIN 792,113

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Electronics_v1_00

A dataset consisting of reviews of Amazon Electronics_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 3,093,869
TRAIN 3,093,869

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Video_Games_v1_00

A dataset consisting of reviews of Amazon Digital_Video_Games_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 145,431
TRAIN 145,431

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Video_Download_v1_00

A dataset consisting of reviews of Amazon Digital_Video_Download_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 4,057,147
TRAIN 4,057,147

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Software_v1_00

A dataset consisting of reviews of Amazon Digital_Software_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 102,084
TRAIN 102,084

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Music_Purchase_v1_00

A dataset consisting of reviews of Amazon Digital_Music_Purchase_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,688,884
TRAIN 1,688,884

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Ebook_Purchase_v1_00

A dataset consisting of reviews of Amazon Digital_Ebook_Purchase_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 12,520,722
TRAIN 12,520,722

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Camera_v1_00

A dataset consisting of reviews of Amazon Camera_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,801,974
TRAIN 1,801,974

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Books_v1_00

A dataset consisting of reviews of Amazon Books_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 10,319,090
TRAIN 10,319,090

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Beauty_v1_00

A dataset consisting of reviews of Amazon Beauty_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,115,666
TRAIN 5,115,666

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Baby_v1_00

A dataset consisting of reviews of Amazon Baby_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 1,752,932
TRAIN 1,752,932

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Automotive_v1_00

A dataset consisting of reviews of Amazon Automotive_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 3,514,942
TRAIN 3,514,942

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Apparel_v1_00

A dataset consisting of reviews of Amazon Apparel_v1_00 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,906,333
TRAIN 5,906,333

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Digital_Ebook_Purchase_v1_01

A dataset consisting of reviews of Amazon Digital_Ebook_Purchase_v1_01 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 5,101,693
TRAIN 5,101,693

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Books_v1_01

A dataset consisting of reviews of Amazon Books_v1_01 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 6,106,719
TRAIN 6,106,719

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls

amazon_us_reviews/Books_v1_02

A dataset consisting of reviews of Amazon Books_v1_02 products in US marketplace. Each product has its own version as specified with it.

Versions:

  • 0.1.0 (default):

Statistics

Split Examples
ALL 3,105,520
TRAIN 3,105,520

Features

FeaturesDict({
    'data': FeaturesDict({
        'customer_id': Tensor(shape=(), dtype=tf.string),
        'helpful_votes': Tensor(shape=(), dtype=tf.int32),
        'marketplace': Tensor(shape=(), dtype=tf.string),
        'product_category': Tensor(shape=(), dtype=tf.string),
        'product_id': Tensor(shape=(), dtype=tf.string),
        'product_parent': Tensor(shape=(), dtype=tf.string),
        'product_title': Tensor(shape=(), dtype=tf.string),
        'review_body': Tensor(shape=(), dtype=tf.string),
        'review_date': Tensor(shape=(), dtype=tf.string),
        'review_headline': Tensor(shape=(), dtype=tf.string),
        'review_id': Tensor(shape=(), dtype=tf.string),
        'star_rating': Tensor(shape=(), dtype=tf.int32),
        'total_votes': Tensor(shape=(), dtype=tf.int32),
        'verified_purchase': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
        'vine': ClassLabel(shape=(), dtype=tf.int64, num_classes=2),
    }),
})

Urls