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NEW QUESTION 44
A vector in vector calculus is a quantity that has magnitude and direction.
What is a vector in computer programming?
- A. A constant
- B. A two-dimensional array of scalars.
- C. An array of complex numbers
- D. An array with one dimension.
Answer: D
Explanation:
Explanation
In computer programming, a vector is a data structure that contains a collection of elements that are all of the same type. Each element in the vector has an associated index, which can be used to access and modify the element at that index. Vectors are commonly used to store collections of numerical values (e.g., integers or floating-point numbers) or strings, but they can also be used to store any type of data.
References: [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, Page number 36 [2] APMG International, “What is a Vector in Computer Programming?”, https://apmg-international.com/en/blog/what-is-a-vector-in-computer-programming/ [3] EXIN, “What is a Vector in Computer Programming?”, https://www.exin.com/blog/what-is-a-vector-in-computer-programming/
NEW QUESTION 45
What does Prof David Chalmers describe the hard consciousness problem to be as comples as?
- A. The universe.
- B. Quantum mechanics.
- C. Turbulence.
- D. Psychology.
Answer: A
Explanation:
Explanation
Prof David Chalmers describes the hard consciousness problem to be as complex as the universe. He argues that understanding consciousness is as hard as understanding the universe itself, due to the number of variables and dimensions involved. He has compared the complexity of the problem to that of turbulence, quantum mechanics, and psychology, but believes that the problem of consciousness is even more complex than all of these.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
David J. Chalmers, “The Hard Problem of Consciousness”, in J. Shear (ed.), Explaining Consciousness: The “Hard Problem”, MIT Press, 1997.
NEW QUESTION 46
What function is used in a Neural Network?
- A. Trigonometric.
- B. Statistical.
- C. Linear.
- D. Activation.
Answer: D
Explanation:
Explanation
Activation Functions
An activation function in 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 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/
NEW QUESTION 47
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