title: what tensorflow.nn.softmax do?
body: <p>I'm following coursera tensorflow course and I can not understand below code can you explain itusing simple english please..</p>
  
  <p>here is code</p>
  
  <pre><code>model = tf.keras.models.Sequential([tf.keras.layers.Flatten(), 
                                  tf.keras.layers.Dense(128, activation=tf.nn.relu), 
                                  tf.keras.layers.Dense(10, activation=tf.nn.softmax)])
  </code></pre>
  
  <p>I want to know what do tf.nn.softmax in a course description have below description but it is not clear to me.</p>
  
  <p>Sequential: That defines a SEQUENCE of layers in the neural network</p>
  
  <p>Flatten: Remember earlier where our images were a square, when you printed them out? Flatten just takes that square and turns it into a 1 dimensional set.</p>
  
  <p>Dense: Adds a layer of neurons</p>
  
  <p>Each layer of neurons need an activation function to tell them what to do. There's lots of options, but just use these for now.</p>
  
  <p>Relu effectively means <strong>"If X>0 return X, else return 0"</strong> -- so what it does it it only passes values 0 or greater to the next layer in the network.</p>
  
  <p>Softmax takes a set of values, and effectively picks the biggest one, so, for example, if the output of the last layer looks like <code>[0.1, 0.1, 0.05, 0.1, 9.5, 0.1, 0.05, 0.05, 0.05]</code>, it saves you from fishing through it looking for the biggest value, and turns it into <code>[0,0,0,0,1,0,0,0,0]</code> -- The goal is to save a lot of coding!</p>