Neural networks with multiple hidden layers are known as?

• A. Shallow networks
• B. Deep learning models
• C. One-layer networks
• D. Convolutional networks

Answer: (B)

Depth in a neural network is what makes it a deep learning model. When a network has multiple hidden layers, it can learn increasingly abstract representations as data passes through each layer. Early layers tend to detect simple features, while deeper layers combine those features into more complex concepts, enabling the handling of sophisticated tasks like image or speech recognition. A shallow network has only one hidden layer and is limited in the complexity it can represent, whereas deep learning models encompass networks with many layers. Convolutional networks are a specific deep learning architecture designed for grid-like data, but the general term for networks with multiple hidden layers is deep learning models.