What are the types of tensors in deep learning?

What are the different types of tensors used in deep learning?

In deep learning, the main types of tensors are scalars, vectors, matrices, and higher-dimensional tensors. Each serves a unique purpose.

Can you explain what a scalar tensor is?

A scalar tensor is a single numerical value, represented as a 0-dimensional tensor. It's the simplest form of a tensor.

What about vector tensors?

Vector tensors are 1-dimensional arrays of numbers. They can represent data points in a feature space.

How do matrix tensors differ from vector tensors?

Matrix tensors are 2-dimensional arrays, allowing for more complex data representation, like images or tabular data.

Are there any higher-dimensional tensors?

Yes, higher-dimensional tensors can have three or more dimensions, often used in deep learning for complex data like videos.