tensorflow keras dataset

자동완성으로 해보니 몇가지 나오는데 mnist 말고는 몰라서 찾아보는 중

>>> tf.keras.datasets. tf.keras.datasets.boston_housing  tf.keras.datasets.cifar100        tf.keras.datasets.imdb            tf.keras.datasets.reuters          tf.keras.datasets.cifar10         tf.keras.datasets.fashion_mnist   tf.keras.datasets.mnist

 

imdb는 영화 db

boston_housing은 statlib 사이트에서 정의된 보스톤 주택가격

reuter는 46 주제에 따른 11228 뉴스(로이터 뉴스) 인 듯.

This is a dataset of 11,228 newswires from Reuters, labeled over 46 topics.

[링크 : https://www.tensorflow.org/api_docs/python/tf/keras/datasets/boston_housing/load_data]

[링크 : https://www.tensorflow.org/api_docs/python/tf/keras/datasets]

 

cifar10은 10개 클래스니까.. 결과도 MNIST 처럼 10개로 나올 것 같고..

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

[링크 : https://www.tensorflow.org/datasets/catalog/cifar10?hl=en]

 

This dataset is just like the CIFAR-10, except it has 100 classes containing 600 images each. There are 500 training images and 100 testing images per class. The 100 classes in the CIFAR-100 are grouped into 20 superclasses. Each image comes with a "fine" label (the class to which it belongs) and a "coarse" label (the superclass to which it belongs).

[링크 : https://www.tensorflow.org/datasets/catalog/cifar100?hl=en]

[링크 : https://www.tensorflow.org/datasets/catalog/fashion_mnist?hl=en]

[링크 : https://www.tensorflow.org/datasets/catalog/emnist?hl=en]