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Artificial Intelligence, Expert Systems and Robotics

Neural network modelling

  • 3 things to know
  • A2 Unit 1

Overview

Neural network and purpose of an activation function.

What you need to know

Answer each one before you reveal it.

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Key term

Describe what a single node in a neural network does.

Key term

What is a neural network?

Key term

Describe the three kinds of layer in a neural network.

Questions from this subtopic

Each one with the model answer underneath.

  1. 1

    What is a neural network?

    Model answer

    A neural network is a model built from many simple interconnected processing units arranged in layers, loosely based on the way neurons in a brain pass signals to one another.

  2. 2

    Describe the three kinds of layer in a neural network.

    Model answer

    A neural network has an input layer that receives the data, one or more hidden layers that transform it, and an output layer that produces the result.

  3. 3

    Describe what a single node in a neural network does.

    Model answer

    A node takes several inputs, multiplies each by the weight on its connection, adds the results together with a bias and passes the total through an activation function to produce its own output.

  4. 4

    What is a weight in a neural network?

    Model answer

    A weight is a number attached to the connection between two nodes that sets how strongly one node's output influences the next, and the weights are what a neural network actually learns.

  5. 5

    State the purpose of an activation function.

    Model answer

    An activation function decides a node's output from its total input, and being non-linear it allows the network as a whole to model relationships that no straight line could represent.

  6. 6

    What is a bias in a neural network?

    Model answer

    A bias is a constant added to a node's weighted total. The constant shifts the point at which that node starts to produce a strong output.

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