| DIFFERENCE BETWEEN | NEURAL NETWORKS | DEEP LEARNING SYSTEMS |
|---|---|---|
| Definition | A neural network is a model of neurons inspired by the human brain. It is made up of many neurons that at inter-connected with each other. | Deep learning neural networks are distinguished from neural networks on the basis of their depth or number of hidden layers. |
| Architecture |
Feed Forward Neural Networks Recurrent Neural Networks Symmetrically Connected Neural Networks |
Recursive Neural Networks Unsupervised Pre-trained Networks Convolutional Neural Networks |
| Structure |
Neurons Connection and weights Propagation function Learning rate |
Motherboards PSU RAM Processors |
| Time & Accuracy |
It generally takes less time to train them. They have a lower accuracy than Deep Learning Systems |
It generally takes more time to train them. They have a higher accuracy than Deep Learning Systems |
