Implementing a single input neuron
In this example, we will take a closer look at TensorFlow's and TensorBoard's main concepts and try to do some basic operations to get you started. The model we want to implement simulates a single neuron. For reference, see the following diagram:
A schema representing the single input neuron
The output will be the input product for the weight.
The preceding schema consists of the following:
- An input value, which stimulates the neuron.
- A single weight, which is multiplied by the input, provides the output of the neuron. The weight value will vary in the course of the training procedure.
- The output is given by the product input
xweight. The neuron will learn when the given output will be issued next to the expected value. - These elements are enough to define the model. The input value represents a stimulus to the neuron. It is a constant which is defined with the TensorFlow operator, that is,
tf.constant.
We define the input_value, which is 0.5 a floating point...
