How to Load IMBD Datasets?
Load Datasets Using TensorFlow
TensorFlow Datasets (TFDS) provides a collection of ready-to-use datasets for use with TensorFlow. Some IMDb datasets are available through TFDS. Use TFDS to load the IMDb dataset (e.g., IMDb reviews for sentiment analysis).
# prompt: Write a code to dispay top 5 imbd dataset in datafame with tensorflow tfds
import pandas as pd
import tensorflow_datasets as tfds
# Load the IMDb reviews dataset
dataset, info = tfds.load('imdb_reviews', with_info=True, as_supervised=True)
train_dataset, test_dataset = dataset['train'], dataset['test']
# Get the top 5 examples from the training dataset
top_5_examples = train_dataset.take(5)
# Create a Pandas DataFrame to display the examples
df = pd.DataFrame(top_5_examples)
# Print the DataFrame
print(df)
Output:
0 tf.Tensor(b"This was an absolutely terrible mo...
1 tf.Tensor(b'I have been known to fall asleep d...
2 tf.Tensor(b'Mann photographs the Alberta Rocky...
3 tf.Tensor(b'This is the kind of film for a sno...
4 tf.Tensor(b'As others have mentioned, all the ...
Load Datasets Using keras Imdb Dataset
Keras, which is now part of the TensorFlow library, provides built-in support for the IMDb dataset, particularly the IMDb movie reviews dataset, which is commonly used for sentiment analysis.
Keras includes the imdb dataset in its datasets module. You can load it directly without needing to manually download it.
# prompt: Write a code to dispay top 5 imbd dataset in datafame with tensorflow.keras.datasets
import pandas as pd
import tensorflow as tf
from tensorflow.keras.datasets import imdb
# Load the IMDb reviews dataset
(train_data, train_labels), (test_data, test_labels) = imdb.load_data(num_words=10000)
# Create a dataframe with the top 5 reviews and labels
df = pd.DataFrame({
'review': train_data[:5],
'label': train_labels[:5]
})
# Display the dataframe
print(df.to_string())
Output:
0 [1, 14, 22, 16, 43, 530, 973, 1622, 1385, 65, 458, 4468, 66, 3941, 4, 173, 36, 256, 5, 25, 100, 43, 838, 112, 50, 670, 2, 9, 35, 480, 284, 5, 150, 4, 172, 112, 167, 2, 336, 385, 39, 4, 172, 4536, 1111, 17, 546, 38, 13, 447, 4, 192, 50, 16, 6, 147, 2025, 19, 14, 22, 4, 1920, 4613, 469, 4, 22, 71, 87, 12, 16, 43, 530, 38, 76, 15, 13, 1247, 4, 22, 17, 515, 17, 12, 16, 626, 18, 2, 5, 62, 386, 12, 8, 316, 8, 106, 5, 4, 2223, 5244, 16, ...] 1
1 [1, 194, 1153, 194, 8255, 78, 228, 5, 6, 1463, 4369, 5012, 134, 26, 4, 715, 8, 118, 1634, 14, 394, 20, 13, 119, 954, 189, 102, 5, 207, 110, 3103, 21, 14, 69, 188, 8, 30, 23, 7, 4, 249, 126, 93, 4, 114, 9, 2300, 1523, 5, 647, 4, 116, 9, 35, 8163, 4, 229, 9, 340, 1322, 4, 118, 9, 4, 130, 4901, 19, 4, 1002, 5, 89, 29, 952, 46, 37, 4, 455, 9, 45, 43, 38, 1543, 1905, 398, 4, 1649, 26, 6853, 5, 163, 11, 3215, 2, 4, 1153, 9, 194, 775, 7, 8255, ...] 0
2 [1, 14, 47, 8, 30, 31, 7, 4, 249, 108, 7, 4, 5974, 54, 61, 369, 13, 71, 149, 14, 22, 112, 4, 2401, 311, 12, 16, 3711, 33, 75, 43, 1829, 296, 4, 86, 320, 35, 534, 19, 263, 4821, 1301, 4, 1873, 33, 89, 78, 12, 66, 16, 4, 360, 7, 4, 58, 316, 334, 11, 4, 1716, 43, 645, 662, 8, 257, 85, 1200, 42, 1228, 2578, 83, 68, 3912, 15, 36, 165, 1539, 278, 36, 69, 2, 780, 8, 106, 14, 6905, 1338, 18, 6, 22, 12, 215, 28, 610, 40, 6, 87, 326, 23, 2300, ...] 0
3 [1, 4, 2, 2, 33, 2804, 4, 2040, 432, 111, 153, 103, 4, 1494, 13, 70, 131, 67, 11, 61, 2, 744, 35, 3715, 761, 61, 5766, 452, 9214, 4, 985, 7, 2, 59, 166, 4, 105, 216, 1239, 41, 1797, 9, 15, 7, 35, 744, 2413, 31, 8, 4, 687, 23, 4, 2, 7339, 6, 3693, 42, 38, 39, 121, 59, 456, 10, 10, 7, 265, 12, 575, 111, 153, 159, 59, 16, 1447, 21, 25, 586, 482, 39, 4, 96, 59, 716, 12, 4, 172, 65, 9, 579, 11, 6004, 4, 1615, 5, 2, 7, 5168, 17, 13, ...] 1
4 [1, 249, 1323, 7, 61, 113, 10, 10, 13, 1637, 14, 20, 56, 33, 2401, 18, 457, 88, 13, 2626, 1400, 45, 3171, 13, 70, 79, 49, 706, 919, 13, 16, 355, 340, 355, 1696, 96, 143, 4, 22, 32, 289, 7, 61, 369, 71, 2359, 5, 13, 16, 131, 2073, 249, 114, 249, 229, 249, 20, 13, 28, 126, 110, 13, 473, 8, 569, 61, 419, 56, 429, 6, 1513, 18, 35, 534, 95, 474, 570, 5, 25, 124, 138, 88, 12, 421, 1543, 52, 725, 6397, 61, 419, 11, 13, 1571, 15, 1543, 20, 11, 4, 2, 5, ...] 0
IMDB Datasets : Types, Usages, and Application
The IMDb dataset refers to a collection of data compiled and provided by IMDb (Internet Movie Database), one of the most comprehensive online databases of movies, TV shows, actors, and production crew information. IMDb is a widely used platform for accessing information about films and television programs, including details such as cast and crew credits, user ratings and reviews, plot summaries, trivia, and more.
Table of Content
- Types of IMDB datasets
- How to Download IMDB Dataset?
- How to Load IMBD Datasets?
- Applications of IMDB Datasets
- Use Cases or Project Ideas using IMDB Dataset
The IMDb dataset typically includes structured data in formats such as CSV (Comma-Separated Values) or JSON (JavaScript Object Notation), containing information about movies, TV shows, actors, directors, genres, ratings, release dates, and other related attributes. These datasets are often used for research, analysis, and development of applications related to the entertainment industry, such as recommendation systems, market research, and academic studies.
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