mnist keras
时间: 2023-08-31 07:12:49 浏览: 39
MNIST is a dataset of handwritten digits that is commonly used for image classification tasks in machine learning. Keras is a high-level neural network API that is commonly used for building deep learning models.
In Keras, the MNIST dataset can be loaded using the `keras.datasets` module. The dataset consists of 60,000 training images and 10,000 test images, each of size 28x28 pixels.
Here's an example code snippet that demonstrates how to load the MNIST dataset in Keras:
```python
import keras
from keras.datasets import mnist
# Load MNIST dataset
(x_train, y_train), (x_test, y_test) = mnist.load_data()
# Print dataset shape
print('x_train shape:', x_train.shape) # (60000, 28, 28)
print('y_train shape:', y_train.shape) # (60000,)
print('x_test shape:', x_test.shape) # (10000, 28, 28)
print('y_test shape:', y_test.shape) # (10000,)
```
Once the dataset is loaded, it can be used to train a neural network model for digit classification. Typical steps for building a neural network model in Keras would include defining the model architecture, compiling the model, fitting the model to the training data, and evaluating the model on the test data.