CCEA A-Level Digital Technology 2650
Systems Analysis and Development Approaches
Design, Development and Testing
Implementation and System Security
Programming
Data, Information and Data Representation
Computer Architecture and Processing Systems
System Software, Application Software and the User Interface
Web Technology and Multimedia
Networks
Databases
Artificial Intelligence, Expert Systems and Robotics
Mobile Technology, Data Mining and Cloud Computing
Individual, Social and Legal Considerations
The Development Project: Analysis and Design
The Development Project: Build, Testing and Evaluation
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.
What is a neural network?
Describe the three kinds of layer in a neural network.
Questions from this subtopic
Each one with the model answer underneath.
- 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
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
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
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
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
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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