Datasets - Keras
https://keras.io/api/datasetsDatasets. The tf.keras.datasets module provide a few toy datasets (already-vectorized, in Numpy format) that can be used for debugging a model or creating simple code examples. If you are looking for larger & more useful ready-to-use datasets, take a look at TensorFlow Datasets. Available datasets MNIST digits classification dataset. load_data ...
dataset module — Surprise 1 documentation
surprise.readthedocs.io › en › stabledataset module. The dataset module defines the Dataset class and other subclasses which are used for managing datasets. Users may use both built-in and user-defined datasets (see the Getting Started page for examples). Right now, three built-in datasets are available: The movielens-100k dataset. The movielens-1m dataset.
Datasets - Spektral
graphneural.network › datasetsspektral.datasets.citation.Citation(name, random_split=False, normalize_x=False, dtype=<class 'numpy.float32'>) The citation datasets Cora, Citeseer and Pubmed. Node attributes are bag-of-words vectors representing the most common words in the text document associated to each node.
Datasets - Spektral
https://graphneural.network/datasetsspektral.datasets.qm9.QM9 (amount= None, n_jobs= 1 ) The QM9 chemical data set of small molecules. In this dataset, nodes represent atoms and edges represent chemical bonds. There are 5 possible atom types (H, C, N, O, F) and 4 bond types (single, double, triple, aromatic).
TensorFlow Datasets
www.tensorflow.org › datasets › overviewDec 15, 2021 · Load a dataset tfds.load. The easiest way of loading a dataset is tfds.load. It will: Download the data and save it as tfrecord files. Load the tfrecord and create the tf.data.Dataset. ds = tfds.load('mnist', split='train', shuffle_files=True) assert isinstance(ds, tf.data.Dataset) print(ds)