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APMG-International Artificial-Intelligence-Foundation Exam - Topic 1 Question 15 Discussion

Actual exam question for APMG-International's Artificial-Intelligence-Foundation exam
Question #: 15
Topic #: 1
[All Artificial-Intelligence-Foundation Questions]

Splitting data into Training and Test data sets is part of what?

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Suggested Answer: B

Reflex and Model-based Reflex are two types of Artificial Intelligent Agents. Artificial Intelligent Agents are computer systems designed to act and think in a manner similar to humans, incorporating elements of problem solving, decision-making, communication, and learning. Reflex agents are reactive agents which act based on the current environment and conditions, while Model-based Reflex agents use a model of the environment to make decisions. Reference: BCS Foundation Certificate In Artificial Intelligence Study Guide,https://bcs.org/ai/certificate/and APMG International,https://www.apmg-international.com/qualifications/artificial-intelligence-foundation-certificate.


by Marshall at Oct 20, 2024, 02:02 AM

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Nobuko
3 months ago
Yeah, splitting data is crucial for training models!
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Kanisha
3 months ago
I thought it was more about post processing, not prep.
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Emily
3 months ago
Wait, is it really that important?
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Dong
4 months ago
Totally agree, A is the right choice.
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Vincent
4 months ago
It's definitely part of machine learning data preparation!
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Lorrine
4 months ago
I’m a bit confused; I thought it might be post processing, but now I’m thinking it’s more about preparing the data before training.
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Roosevelt
4 months ago
I feel like it could be related to batch learning as well, but I lean towards data preparation since it’s a common step.
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Sueann
4 months ago
I remember practicing a question like this, and it was about data preparation too. So, I would go with option A.
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France
5 months ago
I think splitting data is definitely part of machine learning data preparation, but I'm not 100% sure.
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Sherell
5 months ago
I'm a little confused by this question. Is splitting data into training and test sets considered a "machine learning" technique, or is it more of a general data analysis/modeling approach? I'm not 100% sure, so I'll have to make an educated guess on this one.
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Rasheeda
5 months ago
Okay, let me think this through step-by-step. Splitting the data into training and test sets is done before the actual machine learning model is trained, right? So it has to be part of the data preparation process, not post-processing. I'm going to go with A.
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Cecily
5 months ago
Hmm, I'm a bit unsure about this one. I know splitting data is important for machine learning, but I can't quite remember if it's considered part of the data preparation or the post-processing stage. I'll have to think this through carefully.
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Ronnie
5 months ago
This question seems pretty straightforward. I'm pretty confident that the answer is A, since splitting data into training and test sets is a key part of the machine learning data preparation process.
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Mammie
10 months ago
Splitting data? More like 'splitting headaches' when you've got a bunch of messy data to wrangle. But hey, at least it's not rocket science... oh wait.
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Alyce
8 months ago
C) Machine learning post processing.
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Aliza
9 months ago
B) Batch learning.
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Kayleigh
9 months ago
A) Machine learning data preparation.
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Xochitl
10 months ago
D? High performance computing strategy? What kind of sorcery is that? I'll stick with the classic machine learning approach, thank you very much.
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Sharika
9 months ago
D) High performance computing strategy.
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Fanny
9 months ago
C) Machine learning post processing.
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Lonny
9 months ago
B) Batch learning.
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Leatha
9 months ago
A) Machine learning data preparation.
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Katina
10 months ago
Hmm, I was debating between A and B, but A makes more sense. Although, I do enjoy a good batch learning session on the weekends!
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Lilli
10 months ago
I agree, option A is the correct answer. Can't really see how the other options relate to this question at all.
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Pearly
9 months ago
User 2: Yeah, the other options don't really make sense in this context.
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Sage
9 months ago
User 1: I agree, option A is the correct answer.
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Dyan
11 months ago
Splitting data into Training and Test sets is definitely part of machine learning data preparation. This is a classic technique to validate model performance.
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Jame
11 months ago
I agree with Maryann, splitting data into Training and Test data sets is crucial for evaluating the model's performance. So, it must be A) Machine learning data preparation.
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Maryann
11 months ago
I think it's A) Machine learning data preparation because we need to have separate data sets to train and test the model.
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Coral
11 months ago
A) Machine learning data preparation.
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