Tensors — Representation of Data In Neural Networks

What you will learn?

• Tensors
• Key Attributes Of Tensor
• Real-World Examples of Tensors

What is Tensor?

It is a container of Data, which helps to store different dimensions of Data in Neural Networks

Google’s Machine Learning Library TensorFlow was named after them.

Scalar or Rank 0 or 0-D Tensors

• A tensor that contains only one number is called a scalar.
• A Scalar tensor has 0 axes (ndim == 0)
• The number of axes is called a rank of the tensor.

Code :

ignition = tf.Variable(451, tf.int16)

floating = tf.Variable(3.14159265359, tf.float64)

its_complicated = tf.Variable(12.3–4.85j, tf.complex64)

Vector or Rank 1 or 1-D Tensors

• An array of numbers is called a vector, or 1-D Tensor.

Code:

mystr = tf.Variable([“Hello”], tf.string)

cool_numbers = tf.Variable([3.14159, 2.71828], tf.float32)