Loading Data from TensorFlow Datasets

Using TensorFlow Datasets, load the MNIST training and testing data into your program. Additionally, load the dataset information provided by TensorFlow.

1. Display the dataset information provided by TensorFlow.
2. Display the class label names.
3. Display some example images.

1. Normalize image pixel data to values between 0 and 1.
2. Since the dataset is small, load all of it into memory for better performance.
3. Shuffle the training data to help the model generalize, but don't shuffle the test data.
4. Batch the data to make training faster.

1. Create a basic Keras Sequential deep neural network to predict the number in each image.
2. Compile the model with an appropriate optimizer and loss function.
3. Train the model for a few epochs using the training data.
4. Evaluate the model using the test data.
5. Save the model for later use.