Our neurological process uses previous experience as examples, learning a structure to understand the data and form a conclusion or output:
Neurons making connections to go from input to hidden layer to single output
This basic architecture will form the foundation of our deep neural network, which we'll present in the next section.
Here are the basic steps of how the model is built:
- An input (an image or other input data) is sent into an input (static) layer
- The single or series of hidden layer then operates on this data
- The output layer aggregates all of this information into an output format
