Datasets in TensorFlow QUIZ (MCQ QUESTIONS AND ANSWERS)

Stores dataset elements in a cache memory for faster access

Removes elements from the dataset cache

Clears the cache memory

There is no cache() method in TensorFlow datasets

Enumerates all elements of the dataset

Adds enumeration information to dataset elements

Enumerates batches of dataset elements

There is no enumerate() method in TensorFlow datasets

Using the time_series() method

Manually processing time-series data

Using functions in the tf.data.time_series module

There is no built-in method for time-series data processing in TensorFlow datasets

tf.stack()

tf.dataset.concat_axis()

tf.data.concat()

tf.data.Dataset.concatenate()

Groups dataset elements based on a window size

Applies a window function to dataset elements

Windows the dataset based on groupings

There is no group_by_window() method in TensorFlow datasets

Using the tokenize() method

Manually splitting text into tokens

Using functions in the tf.data.text module

There is no built-in method for tokenization in TensorFlow datasets

tf.statistics()

tf.dataset.statistics()

tf.data.Dataset.summary()

There is no built-in method for calculating statistics in TensorFlow datasets

Flattens nested datasets

Maps a function across all elements of the dataset

Maps a function to each nested dataset

There is no flat_map() method in TensorFlow datasets

tf.fill_missing()

tf.dataset.handle_missing()

tf.data.Dataset.fillna()

There is no built-in method for handling missing values in TensorFlow datasets

Using the text_to_numerical() method

Manually encoding text to numerical values

Using functions in the tf.data.text module

There is no built-in method for text encoding in TensorFlow datasets

Inserts empty intervals into the dataset

Alternates between datasets, interleaving their elements

Interpolates missing values in the dataset

There is no interleave() method in TensorFlow datasets

tf.data.Dataset.window()

tf.dataset.window()

tf.data.window()

There is no built-in method for windowing in TensorFlow datasets

Using the normalize() method

Manually calculating mean and standard deviation

Using functions in the tf.data.experimental.preprocessing module

There is no built-in method for normalization in TensorFlow datasets

Reduces the size of the dataset by removing elements

Reduces the dimensionality of the dataset elements

Applies a reduction operation to the dataset elements

There is no reduce() method in TensorFlow datasets

tf.dataset.process()

tf.data.process()

tf.data.Dataset.map()

tf.dataset.map()

tf.datasets

tf.data.datasets

tf.keras.datasets

tf.datasets.builtin

tf.filter()

tf.data.filter()

tf.data.Dataset.filter()

tf.dataset.filter()

Repeats the dataset indefinitely

Repeats each element of the dataset a certain number of times

Repeats a specified number of elements from the dataset

There is no repeat() method in TensorFlow datasets

tf.data.augment()

tf.dataset.augment()

tf.data.Dataset.map()

tf.data.experimental.preprocessing()

Returns the first element of the dataset

Removes a specified number of elements from the dataset

Takes a specified number of elements from the dataset

Extracts elements based on a given condition

tf.data.Dataset.prefetch()

tf.prefetch()

tf.dataset.prefetch()

tf.data.prefetch()

Using the split() method

Manually selecting elements for training and testing

Using the train_test_split() function

There is no built-in function for dataset splitting

tf.concat()

tf.dataset.concat()

tf.data.concatenate()

tf.data.Dataset.concatenate()

Maps dataset elements to a new dataset

Plots the dataset elements on a map

Filters out certain elements from the dataset

Calculates statistical measures of the dataset

tf.dataset.batch()

tf.data.batch()

tf.batch()

tf.data.Dataset.batch()

Sorts the dataset alphabetically

Randomly shuffles the elements of the dataset

Rearranges the dataset in reverse order

Removes duplicate elements from the dataset

tf.preprocessing

tf.data.preprocessing

tf.dataset.processing

tf.data.experimental

tf.dataset.load_cifar10()

tf.data.load_cifar10()

tf.keras.datasets.cifar10.load_data()

tf.data.cifar10.load()

tf.load_mnist()

tf.data.load_mnist()

tf.keras.datasets.load_mnist()

tf.dataset.load_mnist()

tf.custom.datasets

tf.data.custom_dataset

tf.dataset.create

tf.data.Dataset.from_tensors