Answers.Body: <p>If you do not specify an activation for a layer you are effectively creating a linear transformation through that layer.  From the documentation:</p>
  <blockquote>
  <p><strong>activation:</strong> Activation function to use. If you don't specify anything, no activation is applied (see keras.activations).</p>
  </blockquote>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-01-16T22:12:07.047Z
Answers.LastActivityDate: 2021-01-16T22:12:07.047Z
Answers.UserDisplayName: David Hoelzer
Body: <p>What if I don't apply an activation function on some layers in a neural network. How will it affect the model?</p>
  <p>Take for instance the following code snippet:</p>
  <pre><code>def model(x):
      a = Conv2D(64, (3, 3))(x)                         
      x = Conv2D(64, (3, 3), activation = 'relu')(x)
      b = Conv2D(128, (3, 3))(x)
      x = Conv2D(128, (3, 3), activation = 'relu')(b)
      return x, a, b
  </code></pre>
  
Tags: <machine-learning><deep-learning><convolutional-neural-networks><keras><activation-functions>
Title: What happens if there is no activation function in some layers of a neural network?
UserDisplayName: Akhilesh Sharma
ThreadText: # What happens if there is no activation function in some layers of a neural network?
  
  (Asked by: username_0 on 2021-01-16)
  
  What if I don't apply an activation function on some layers in a neural network. How will it affect the model?
  
  Take for instance the following code snippet:
  
  ```
  def model(x):
      a = Conv2D(64, (3, 3))(x)                         
      x = Conv2D(64, (3, 3), activation = 'relu')(x)
      b = Conv2D(128, (3, 3))(x)
      x = Conv2D(128, (3, 3), activation = 'relu')(b)
      return x, a, b
  
  ```
  
  **Tags:** machine-learning, deep-learning, convolutional-neural-networks, keras, activation-functions
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-01-16. Score: 2
  
  If you do not specify an activation for a layer you are effectively creating a linear transformation through that layer. From the documentation:
  
  > **activation:** Activation function to use. If you don't specify anything, no activation is applied (see keras.activations).
  
  
  ---
  
  