Neural Networks can look super complicated.
But they are all made from simple elements.
Let me explain the building blocks of a neural network.
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Neural networks have two main parts:
- Nodes or Neurons
- Connections between the nodes
Here is a simple example below.
Neural Networks are usually organized in Layers. What are those?
We can group the different nodes into layers:
- Input nodes are in the input layers
- Output nodes are in the output layers
Between input and output, we have the hidden layers.
Let's see two examples:
- A simple Neural Network with single input and output nodes and a single hidden layer with 2 nodes.
- A more complex one with 2 input nodes, 2 hidden layers with 6 nodes, and 2 output nodes.
When you work with Neural Networks, you need to decide
how many hidden layers to use and how many nodes the hidden layers should contain.
Generally, more complex NNs (more layers and nodes) can fit complex data better.