Indian J Pharm Close
 

Figure 3: Simple pictographic representation of (a) machine learning and (b) deep learning. The first layer (input) represents the observed values or data fed into the system. The last layer (output) produces a value or information or class prediction. The intervening layers between the input and output layers are called hidden layers, since they do not correspond to observable data. The tiered structure of the neural networks allows them to produce much more complex output data. The number of intervening neural networks between 'input' and 'output' are much higher in 'deep learning'

Figure 3: Simple pictographic representation of (a) machine learning and (b) deep learning. The first layer (input) represents the observed values or data fed into the system. The last layer (output) produces a value or information or class prediction. The intervening layers between the input and output layers are called hidden layers, since they do not correspond to observable data. The tiered structure of the neural networks allows them to produce much more complex output data. The number of intervening neural networks between 'input' and 'output' are much higher in 'deep learning'