Implementing Activation Functions
Getting ready
When we start to use neural networks, we will use activation functions regularly because activation functions are a mandatory part of any neural network. The goal of the activation function is to adjust weight and bias. In TensorFlow, activation functions are non-linear operations that act on tensors. They are functions that operate in a similar way to the previous mathematical operations. Activation functions serve many purposes, but a few main concepts is that they introduce a non-linearity into the graph while normalizing the outputs. Start a TensorFlow graph with the following commands:
import tensorflow as tf sess = tf.Session()
How to do it…
The activation functions live in the neural network
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