Gal Curious

I've heard about tensors in programming, but what are they? 🤔

Geek Smiling

Tensors are multi-dimensional arrays used to represent data in machine learning and deep learning.

Gal Happy

Oh, I see! Can you help me understand them better?

Geek Nodding

Of course! Let's start with the basics.

Step 1: Scalars, Vectors, and Matrices

Gal Wondering

So, what's the relationship between tensors, scalars, vectors, and matrices?

Geek Smiling

Great question! Scalars are single numbers, vectors are 1D arrays, matrices are 2D arrays, and tensors are 3D or higher-dimensional arrays.

Gal Surprised

Wow, so tensors include all of those! 🤯

Step 2: Creating Tensors

Gal Eager

How do I create a tensor?

Geek Happy

You can use libraries like NumPy or PyTorch to create tensors. Let's create a tensor using PyTorch.

import torch

tensor = torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])

Step 3: Understanding Tensor Properties

Gal Curious

What properties do tensors have?

Geek Smiling

Tensors have a shape, size, and dtype (data type). Let's check these properties for our tensor.



torch.Size([2, 2, 2])
torch.Size([2, 2, 2])

Step 4: Tensor Operations

Gal Excited

Can I perform operations on tensors?

Geek Nodding

Definitely! You can perform various operations, like addition, multiplication, and reshaping. Let's add two tensors together.

tensor1 = torch.tensor([1, 2, 3])
tensor2 = torch.tensor([4, 5, 6])

result = tensor1 + tensor2


tensor([5, 7, 9])


You now understand tensors! Tensors are multi-dimensional arrays that include scalars, vectors, and matrices. They have properties like shape, size, and dtype, and you can perform various operations on them. Keep exploring tensors and have fun! 🚀