I didn’t know it…
-----------------

![](https://hackernoon.com/hn-images/1*_-U7OfMq_DVCzsRuluU6Fw.png)

We all know how to work with tensorflow library and make some amazing models like “cat-dog gif below” leading to great predictions 💯. But what the hell is a tensor?

Maybe you know it… But I didn’t know it.

> Updated-Deep Learning is an attempt to copy the pattern detection ability of a human brain, the main cause of pattern detection is Neural Networks in our brain.

![](https://hackernoon.com/hn-images/1*zNXeQ6mD5z5VD8coStye0w.gif)

[Source](https://www.google.co.in/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwitmOfMwJjWAhUEuI8KHaC0B70QjRwIBw&url=https%3A%2F%2Fsourcedexter.com%2Fquickly-setup-tensorflow-image-recognition%2F&psig=AFQjCNECC-bU3aVXpskLqFb5wTh9hC5KSg&ust=1505059427589200)

#### What is Tensor?

It is **just a general term for unit of data.** Duh… we all know it…

It is also represented with a **Rank**, like in Matrix. They are [g](https://en.wikipedia.org/wiki/Geometry "Geometry")eometric objects that describe linear relations between [geometric](https://hackernoon.com/tagged/geometric) vectors, scalars, and other tensors.

Updated-A tensor consists of a set of primitive values shaped into an array of any number of dimensions.

#### But which type of data, Scalar or Vector?

If you think like me, that it is an upgrade of vectors like vectors is an upgrade to scalars. Then no, you are wrong. **Both** the quantities Scalar and Vector are Tensors.

#### What is a Rank or Tensor’s Rank?

The **number of dimensions** used to [represent](https://hackernoon.com/tagged/represent) the data is known as its Rank.

#### How does it look?

Updated-

**rank/dimension zero tensor** or a **Scalar.**

      5        # The shape is []

A **rank/dimension 1** **tensor** or a **Vector**.

      [ 1., 2., 3., 4. ]     # The shape is [4]

A **rank/dimension 2 tensor** or a **Matrix**. This is 2D _just like a photo with X axis and Y axis._

 # Matrix of **shape \[ 2, 4\]**  
   
 \[ \[ 1., 2., 3., 4. \], \[ 5., 6., 7., 8. \] \]  
  

A **rank/dimension 3 tensor** or a **Tensor**. This is 3D _just like real world with X, Y and Z axis._ Simply, it is just _matrices inside a bigger matrix_.

 # Tensor of **shape \[ 2, 1, 4 \]**

 **\[** \[ **\[** 1., 2., 3., 4. **\]** \]**,** \[ **\[** 5., 6., 7., 8. **\]** \] **\]** 

This is how you can increase the dimensionality of a tensor. 😃

> Tensor a mathematical object analogous to but more general than a vector, represented by an array of components that are functions of the coordinates of a space.

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