Neural Networks and Artificial Intelligence Quiz

Study Notes

Neural networks are a type of artificial intelligence that allow computers to learn how to analyze data in the same way that the human brain does.
Supervised learning is a method of developing artificial intelligence that involves training a computer on input data that has been labeled for a certain output.
Unsupervised learning is a method of using artificial intelligence (AI) systems to find patterns in data sets including data points that are neither categorized nor labeled.
Reinforcement learning is a type of artificial intelligence where the computer learns to operate within the environment by being rewarded for correct actions.
The human brain contains 86 billion neurons and over 100 trillion connections that transmit electrical information throughout the body. The number of neurons in the artificial neural network is far lower.
The primary distinction is that humans forget, whereas neural networks do not. A neural network that has been properly trained.
Artificial constructions can’t even come close to matching the efficiency level of a biological brain, which operates on roughly 20 watts.
A neural network is a computer model that simulates the workings of the brain.
A neural network is made up of a large number of interconnected neurons.
Each neuron can be either activated or not activated.
The activation of a neuron is determined by the input data that it receives.
The output of a neural network is usually a set of values that represent the output of the neural network.
A neural network can be used to solve problems that are too difficult for a computer to solve.

Description

Test your knowledge of neural networks and artificial intelligence with this quiz covering topics such as supervised learning, unsupervised learning, reinforcement learning, and the structure and function of neural networks.