Tensorflow is mostly used for building deep learning models. There are many functions that allow you to manipulate data to make the best predictive model. The TensorFlow * reduce_mean* is one of them. In this entire tutorial, you will know the implementation of TensorFlow tf.reduce_mean with various examples.

## Examples on tf reduce_mean

In this section, you will know all the examples of the TensorFlow * reduce_mean()* function. The reuduce_mean function calculates the mean of elements across dimensions of a tensor.

Please note that I am doing all the coding demonstrations on Jupyter Notebook. For better understanding do the example on your Jupyter Notebook.

### Example 1: Applying tf.reduce_mean on Single Dimension

In this example, firstly I will create a sample tensor of a single dimension and then calculate the mean of all the elements present in the tensor.

Just execute the below lines of code and see the output.

```
import tensorflow as tf
tensor = tf.constant([10,20,30,40])
mean = tf.reduce_mean(tensor)
print(mean)
```

Here I am creating a sample tensor using the * tf.constant() *method and lastly applying

*on it. You will get the following output when you will run the code.*

**reduce_mean()****Output**

### Example 2: Apply reduce_mean on Multi Dimension

In this example, I will create a multi-dimensional tensor and apply the* reduce_mean* on it. There are two ways you can find mean on multi-dimensional tensor. The one is finding mean row-wise and the other is finding mean columnwise. I will show you the examples of both.

#### Finding mean row-wise

For finding the mean for all the elements row-wise you have to pass the axis value as 0.

Execute the below lines of code to calculate the mean.

```
import tensorflow as tf
tensor = tf.constant([[10,20,30,40],[50,60,70,80]])
mean = tf.reduce_mean(tensor,axis=0)
print(mean)
```

**Output**

#### Finding mean column-wise

In the same way, you can find mean of tensor column-wise by passing the value of the axis to 1. Run the below lines of code and see the output.

```
import tensorflow as tf
tensor = tf.constant([[10,20,30,40],[50,60,70,80]])
mean = tf.reduce_mean(tensor,axis=1)
print(mean)
```

**Output**

If you directly apply the * tf.reduce_mean()* without passing the axis value. Then it will find the mean of the entire elements present in the tensor.

## Conclusion

The mean of tensors will generally be used while building your deep learning model. These are examples of how to use the TensorFlow* reduce_mean()* function. I hope you have liked this tutorial. If you have any queries then you can contact us for more help.

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