Hey Community,
Today we are going on with the second part.
You can find all previous posts in this list:
| Part | Headline | Steemit Link: |
|---|---|---|
| I | Introduction | https://steemit.com/neuronalnetwork/@haggy2k3/neuronal-networks-part-1-introduction |
| II | Units | Current Document |
| III | Connections | https://steemit.com/science/@haggy2k3/neuronal-networks-part-iii-connections |
| IV | Inputs | https://steemit.com/science/@haggy2k3/neuronal-networks-part-iv-inputs |
| V | Activities and Outputs | |
| VI | Training and Test | |
| VII | Metrics | |
| VIII | Learning Rules | |
| IX | Types of NN | |
| X | Features of NN | |
| XI | Use Cases | |
| XII | Bonus: Getting started with Membrain |
Neural networks consist of several neurons. These neurons are also referred to
as units, units or nodes. They are used to collect information from the
environment or from other neurons and to forward it to other units or the
environment in a modified form.
In this picture you can see the three different types of neurons:
Input units (the red ones in the picture):
Hidden units (the yellow ones in the picture):
Output units (the green ones in the picture):
nodes within the same vertical order (for example, the two output units on the
right in the figure) are grouped together as a layer.
If you like this post and you want to read more please upvote, resteem and/or follow my blog.
Best regards
Haggy2k3
