A deep neural network (DNN) is a neural network with more than one hidden layer. Those hidden layers transform information between the input and the output; the word “deep” describes this layered structure, not human-like thinking.
What makes a neural network “deep”?
Google for Developers defines a deep neural network as “a neural network containing more than one hidden layer.” It also uses “deep model” to mean a deep neural network. Google’s Machine Learning Glossary
As an Amazon Associate I earn from qualifying purchases.
A neural network maps an input to an output or prediction. The input layer receives information, hidden layers process it, and the output layer produces the result. During training, the network adjusts learned weights and biases that shape how information is transformed from input to output. IBM’s overview of neural networks
The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →How are layers counted?
Layer-count conventions can differ, so it helps to say which one is being used. Under Google’s glossary convention, depth is the total of hidden layers, output layers, and any embedding layers; the input layer is excluded. Google illustrates this with a network containing five hidden layers and one output layer, which it calls a depth of six. That is an example of its counting rule, not a universal threshold or a performance measure. Google’s definition of depth
#1 Best Overall
What “deep” does—and does not—mean
“Deep” refers to the number and arrangement of layers in the model. It does not mean the network thinks or understands in the same way a human brain does. Descriptions of deep learning do not all use identical layer-count wording, which is why a stated convention is more precise than treating one count as universal. IBM’s overview of deep learning
Quick Recap
Best Value
Rank #3
Rank #2
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
