Given above is a description of a neural network. When does a neural network model become a deep learning model?

when you add more hidden layers and increase depth of neural network
when there is higher dimensionality of data
when the problem is an image recognition problem
when there is lower dimensionality of data

The correct answer is A. when you add more hidden layers and increase depth of neural network.

A neural network is a type of machine learning algorithm that is inspired by the human brain. It consists of a number of interconnected nodes, or neurons, that can learn to recognize patterns in data. The more hidden layers a neural network has, the more complex patterns it can learn to recognize.

Deep learning is a type of machine learning that uses neural networks with multiple hidden layers. Deep learning algorithms have been shown to be very effective at a variety of tasks, including image recognition, natural language processing, and speech recognition.

Option B is incorrect because the dimensionality of the data does not affect whether a neural network is a deep learning model. Option C is incorrect because the type of problem does not affect whether a neural network is a deep learning model. Option D is incorrect because the dimensionality of the data does not affect whether a neural network is a deep learning model.