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BCS Exam AIF Topic 3 Question 42 Discussion

Actual exam question for BCS's AIF exam
Question #: 42
Topic #: 3
[All AIF Questions]

What function is used in a Neural Network?

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Suggested Answer: B

Activation Functions

Anactivation functionin a neural network defines how the weighted sum of the input is transformed into an output from a node or nodes in a layer of the network.

https://machinelearningmastery.com/choose-an-activation-function-for-deep-learning/#:~:text=An%20activation%20function%20in%20a,a%20layer%20of%20the%20network.

An activation function is a mathematical function used in a neural network to determine the output of a neuron. Activation functions are used to transform the inputs into an output signal and can range from simple linear functions to complex non-linear functions. Activation functions are an important part of neural networks and help the network learn patterns and generalize data. Types of activation functions include sigmoid, ReLU, tanh, and softmax. References: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/certifications/foundation-certificates/artificial-intelligence/


by Salena at Jul 16, 2024, 08:32 AM

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Lyla
3 months ago
Haha, D. Trigonometric. Because who doesn't love a little sine and cosine in their neural networks?
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Gerald
3 months ago
B, Activation, no doubt. Gotta have those fun, non-linear functions to get those neurons firing!
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Wai
3 months ago
Definitely B. Activation functions are the secret sauce that make neural networks work their magic.
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Deeanna
2 months ago
I'm not sure, maybe C) Statistical?
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Cordie
2 months ago
No, it's definitely B) Activation.
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Isadora
2 months ago
I think it's A) Linear.
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Cammy
2 months ago
I agree, activation functions are crucial for neural networks.
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Fabiola
3 months ago
Hmm, I'd go with B. Activation functions are the real MVPs of neural nets, transforming those raw inputs into something meaningful.
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Ryann
2 months ago
Yeah, without activation functions, the neural network would just be a series of linear operations.
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Frederic
2 months ago
I agree, activation functions are crucial for adding non-linearity to the network.
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Micaela
3 months ago
I believe it's B) Activation because it introduces non-linearity to the network.
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Daniel
3 months ago
I'm not sure, but I think it might be A) Linear.
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Tiffiny
4 months ago
I'm pretty sure it's B, Activation. That's the one that lets the network make sense of all the inputs.
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Youlanda
2 months ago
D) Trigonometric seems less likely to be used in a neural network.
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Alesia
3 months ago
C) Statistical might be used for analyzing data within the network.
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Annice
3 months ago
I think A) Linear is also important for certain calculations in the network.
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Keneth
3 months ago
I agree, B) Activation is crucial for the neural network to process inputs.
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Allene
4 months ago
Activation functions are the heart of neural networks, like the beating pulse that brings them to life!
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Mozell
2 months ago
C) Statistical.
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Jannette
3 months ago
B) Activation.
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Keena
3 months ago
A) Linear.
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Frank
3 months ago
C) Statistical.
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Iraida
3 months ago
B) Activation.
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Teddy
4 months ago
A) Linear.
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Luisa
4 months ago
I agree with Oneida, Activation function is crucial for Neural Networks.
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Oneida
4 months ago
I think the answer is B) Activation.
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