AIF問題集PDFは最新 [2022年最新] 究極な学習ガイド
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質問 20
What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?
- A. Automation
- B. Big Data
- C. Al personal assistants.
- D. Enhanced design.
正解: B
解説:
Explanation
https://research.com/careers/what-is-the-fourth-industrial-revolution
質問 21
An agent based model is a simul-ation of autonomous agents (individual and collective). What can be used to learn from the data generated by the simul-ations?
- A. Python.
- B. Paraview.
- C. A spreadsheet
- D. Machine Learning.
正解: C
解説:
https://www.pnas.org/doi/10.1073/pnas.082080899
質問 22
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Over-fitting
- B. Iteration.
- C. Activation.
- D. Boosting.
正解: D
解説:
Explanation
* Weak Learner: Colloquially, a model that performs slightly better than a naive model.
More formally, the notion has been generalized to multi-class classification and has a different meaning
beyond better than 50 percent accuracy.
For binary classification, it is well known that the exact requirement for weak learners is to be better than
random guess. [...] Notice that requiring base learners to be better than random guess is too weak for
multi-class problems, yet requiring better than 50% accuracy is too stringent.
- Page 46, Ensemble Methods, 2012.
It is based on formal computational learning theory that proposes a class of learning methods that possess
weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as
a simplification of the more desirable strong learnability, where a learnable achieved arbitrary good
classification accuracy.
A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to
achieve arbitrarily high accuracy; a weak learning algorithm needs only output an hypothesis that performs
slightly better (by an inverse polynomial) than random guessing.
- The Strength of Weak Learnability, 1990.
It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble
learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak
learners as opposed to strong, at least in the colloquial meaning of the term.
More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.
The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.
https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble-learning/
質問 23
The Scrum Master is part of which team?
- A. Agile project team.
- B. Data preparation team
- C. Management team
- D. Software development team.
正解: A
解説:
Explanation
https://www.techtarget.com/whatis/definition/scrum-master#:~:text=A%20Scrum%20Master%20is%20a,in%20a
質問 24
Para View allows large data sets to be visualised on a parallel computer.
Which of the following is one of the techniques used?
- A. Contour plot
- B. Dashboard.
- C. Eigen function analysis.
- D. Norm calculation.
正解: A
質問 25
The EU and United Nations have made designing for all individuals a core principle. What is this type of
design called?
- A. Biophilic design.
- B. Utopic design.
- C. Universal design.
- D. Core design
正解: C
解説:
Explanation
https://universaldesign.ie/What-is-Universal-Design/
質問 26
In Machine learning what are a brain's axons called?
- A. Dendrites
- B. Edges
- C. Nodes
- D. Tetrahedra.
正解: A
質問 27
Tensor flow is a typical open source what?
- A. Agent based modelling application
- B. Machine learning library.
- C. Intelligent robot paradigm.
- D. Cloud based AI application.
正解: B
解説:
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
https://www.tensorflow.org/#:~:text=TensorFlow%20is%20an%20end%2Dto,and%20deploy%20ML%20powered%20applications.
質問 28
What does TRL stand for?
- A. Technical Robotic Level.
- B. Transform Reinforced Learning
- C. Technology Readiness Level.
- D. Transport Ready Level.
正解: C
解説:
Explanation
Technology Readiness Level (TRL) Technology Readiness Levels (TRL) are a method of estimating the
technology maturity of Critical Technology Elements (CTE) of a program during the acquisition process.
https://acqnotes.com/acqnote/tasks/technology-readiness-level#:~:text=Technology%20Development-,Technolog
質問 29
Splitting data into Training and Test data sets is part of what?
- A. High performance computing strategy.
- B. Machine learning data preparation.
- C. Machine learning post processing.
- D. Batch learning.
正解: B
質問 30
In an Al project the domain expert is the person...
- A. who measures the trustworthiness of the Al system
- B. with technical and managerial oversight of the business plan
- C. whomanages the agile project and writes the technical terms of reference
- D. with special knowledge or skills in the area of endeavour and defines what is fit for purpose'
正解: A
質問 31
Which of the following is an advantage of a machine based system?
- A. Able to judge ambiguous and unknown situations.
- B. Undertakes monotonous tasks reliably and accurately.
- C. Can explain the output of an Al system
- D. Capable of sympathising with humans.
正解: B
質問 32
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. A production line.
- B. An autonomous vehicle.
- C. A computer.
- D. A robot
正解: D
解説:
Explanation
https://en.wikipedia.org/wiki/Robot#:~:text=A%20robot%20is%20a%20machine,control%20may%20be%20em
質問 33
An Al agent relies on its perceptual input. This is called the agent's what?
- A. Environment
- B. Percept
- C. World
- D. Position
正解: B
解説:
Agent Terminology
Performance Measure of Agent − It is the criteria, which determines how successful an agent is.
Behavior of Agent − It is the action that agent performs after any given sequence of percepts.
Percept − It is agent's perceptual inputs at a given instance.
Percept Sequence − It is the history of all that an agent has perceived till date.
Agent Function − It is a map from the precept sequence to an action.
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_agents_and_environments.htm
質問 34
Which of the following is an example of fitting a curve to a set of data?
- A. Least squares regression.
- B. Python.
- C. Backward propagation.
- D. Bayesian network.
正解: A
質問 35
If Al undertakes routine and monotonous tasks and takes these away from humans, what will humans do?
- A. Higher value work.
- B. Change jobs.
- C. Leisure activities
- D. Sabotage the Al.
正解: A
質問 36
Tensor flow is a typical open source what?
- A. Agent based modelling application
- B. Machine learning library.
- C. Intelligent robot paradigm.
- D. Cloud based AI application.
正解: B
解説:
Explanation
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible
ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and
developers easily build and deploy ML powered applications.
https://www.tensorflow.org/#:~:text=TensorFlow%20is%20an%20end%2Dto,and%20deploy%20ML%20power
質問 37
In an Al project the domain expert is the person...
- A. who manages the agile project and writes the technical terms of reference
- B. who measures the trustworthiness of the Al system
- C. with technical and managerial oversight of the business plan
- D. with special knowledge or skills in the area of endeavour and defines what is fit for purpose'
正解: B
質問 38
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Over-fitting
- B. Iteration.
- C. Activation.
- D. Boosting.
正解: D
解説:
Weak Learner: Colloquially, a model that performs slightly better than a naive model.
More formally, the notion has been generalized to multi-class classification and has a different meaning beyond better than 50 percent accuracy.
For binary classification, it is well known that the exact requirement for weak learners is to be better than random guess. [...] Notice that requiring base learners to be better than random guess is too weak for multi-class problems, yet requiring better than 50% accuracy is too stringent.
- Page 46, Ensemble Methods, 2012.
It is based on formal computational learning theory that proposes a class of learning methods that possess weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as a simplification of the more desirable strong learnability, where a learnable achieved arbitrary good classification accuracy.
A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to achieve arbitrarily high accuracy; a weak learning algorithm needs only output an hypothesis that performs slightly better (by an inverse polynomial) than random guessing.
- The Strength of Weak Learnability, 1990.
It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak learners as opposed to strong, at least in the colloquial meaning of the term.
More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.
The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.
https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble-learning/
質問 39
What is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a
class of problems?
- A. A paradigm.
- B. An approach.
- C. An algorithm.
- D. A set
正解: A
質問 40
Human-centric trustworthy Al must be...
- A. financially sustainable.
- B. tested by humans.
- C. continually assessed and monitored.
- D. quality assurance certified.
正解: D
質問 41
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what
type of machine learning?
- A. Big Data learning.
- B. Online learning.
- C. Patchwork learning.
- D. Batch learning.
正解: A
質問 42
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Artificial General Intelligence.
- B. Human.
- C. Machine.
- D. Human plus machine.
正解: A
質問 43
Reflex and Model-based Reflex are two types of what?
- A. Robot
- B. Artificial intelligent agents.
- C. Compilers.
- D. Algorithms.
正解: B
質問 44
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