How do tensors impact deep learning performance?

What role do tensors play in deep learning?

Tensors are multi-dimensional arrays that store data in deep learning models, enabling efficient computation.

How do tensors improve the performance of neural networks?

Tensors allow for parallel processing and efficient memory usage, which speeds up training and inference in neural networks.

Can you explain the difference between tensors and traditional data structures?

Unlike traditional data structures, tensors can represent data in multiple dimensions, making them more suitable for complex data like images and videos.

What are some common operations performed on tensors?

Common operations include addition, multiplication, reshaping, and slicing, which are essential for manipulating data in deep learning.