person Author: Process Fellows
Tensors are the basic building blocks of machine learning. They are multidimensional arrays that generalize scalars, vectors and matrices. They are used in deep learning, especially for data such as images, texts or time series.
Examples:

• Image processing (3D tensor):
  • Colored (RGB) picture is stored as: Width x Height x RGB Colors
  • 3D tensor with (256,256,3)
• Training data of 32 pictures, each picture of 28 pixels x 28 pixels and one grayscale channel:
  • 4D tensor (32,28,28,1)