Questions and Answers
Which of the following is true about artificial neural networks?
They model connections of biological neurons as weights between nodes
What is the acceptable range of output for an artificial neural network?
0 and 1, or it could be −1 and 1
What is the purpose of an activation function in an artificial neural network?
To control the amplitude of the output
What does a positive weight in an artificial neural network indicate?
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What can artificial neural networks be trained via?
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Study Notes
Artificial Neural Networks
- Artificial neural networks can be trained via supervised learning, unsupervised learning, and reinforcement learning.
- The acceptable range of output for an artificial neural network is typically between 0 and 1.
- The purpose of an activation function in an artificial neural network is to introduce non-linearity into the model, allowing it to learn more complex relationships between inputs and outputs.
- A positive weight in an artificial neural network indicates an excitatory connection, meaning the input increases the likelihood of the neuron firing.
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