TensorFlow create dataset from numpy array

Question

TensorFlow as build it a nice way to store data. This is for example used to store the MNIST data in the example:

>>> mnist

<tensorflow.examples.tutorials.mnist.input_data.read_data_sets.<locals>.DataSets object at 0x10f930630>

Suppose to have a input and output numpy arrays.

>>> x = np.random.normal(0,1, (100, 10))

>>> y = np.random.randint(0, 2, 100)

How can I transform them in a tf dataset?

I want to use functions like next_batch

Answer 1

The Dataset object is only part of the MNIST tutorial, not the main TensorFlow library. Datasets For Machine Learning would be required quite extensively in order to understand this course.

The constructor accepts an image and labels argument so presumably, you can pass your own values there. This will also enable one to understand the basics of Machine Learning Tutorials.