Product_Review_Keras_Model

Install Tensorflow == 1.2.0

IMDB - review

Description:

Large Movie Review Dataset. 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. There is additional unlabeled data for use as well.

Homepage: http://ai.stanford.edu/~amaas/data/sentiment/

Source code: tfds.text.imdb.IMDBReviews

Versions:1.0.0 (default): New split API (https://tensorflow.org/datasets/splits)

Download size: 80.23 MiB

Dataset size: Unknown size

Auto-cached (documentation): No

Splits:

Split Examples: 'test' 25,000, 'train' 25,000, 'unsupervised' 50,000, Supervised keys (See as_supervised doc): ('text', 'label')

import tensorflow_datasets as tfds

ds = tfds.load('imdb_reviews', split='train')

for ex in ds.take(4):

print(ex)