What is the difference between tensors and matrices?

What is the difference between tensors and matrices?

Tensors are generalizations of matrices. While matrices are 2D arrays, tensors can have multiple dimensions.

Can you give me an example of a tensor?

Sure! A 3D tensor can represent a color image, where each pixel has three values (RGB) across width, height, and color channels.

Are all matrices also tensors?

Yes, all matrices are tensors of rank 2. Tensors can be of any rank, including scalars (rank 0) and vectors (rank 1).

How do tensors apply in machine learning?

Tensors are fundamental in machine learning, especially in deep learning, as they represent data inputs, weights, and outputs.