Neural Network

_________ type of model, the algorithm learns from a dataset which is labelled, and the algorithm uses the answer keys to evaluate its accuracy on the training data.

• Supervised learning

• UnSupervised learning

• Reinforcement learning

In this type of model, the algorithms work towards accomplishing the goal or try to improve the performance in a particular task. This is used in gaming.

• Reinforcement learning

• Supervised Learning

• UnSupervised Learning

•In this type of model, the algorithm learns and makes sense by extracting features/patterns from the unlabelled dataset provided (The system will evaluate by itself)

• Unsupervised learning

• supervised learning

• Reinforcement learning

Information flows from

Input layer -> Hidden Layer-> Output layer

• Feedforward Network

• Backpropagation

Every Artificial Neural must have at least ______

• two layers.

• three layers.

• four layers.

The neurons in the human brain regularly change their threshold.

• True

• False

The current Artificial Neural Networks are part of _____.

• Weak Al systems.

• Strong Al systems.

• Future Al systems.

How many output layers are required for constructing an Artificial Neural Network?

• 1

• 3

• 2

Conventional Computing is deterministic in nature while Neural Computing is Probabilistic in nature.

• True

• False

Backpropagation calculates the ____ and propagates it back to earlier layers.

• value

• error

• data