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BCS AIF Exam - Topic 8 Question 47 Discussion

With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
D) Online learning.
A) Batch learning.
B) Big Data learning.
C) Patchwork learning.

BCS AIF Exam - Topic 8 Question 47 Discussion

Actual exam question for BCS's AIF exam
Question #: 47
Topic #: 8
[All AIF Questions]

With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?

Show Suggested Answer Hide Answer
Suggested Answer: D

Online learning is a type of machine learning that can be used when a large dataset is limited in computational resources or if the data is frequently changing. It allows the system to learn from new data as it is being presented, rather than having to re-train the entire dataset each time new data is added. This makes it more efficient and effective than batch learning, as it only needs to process the new data and not the entire dataset. Online learning is often used in applications such as fraud detection, where new data is constantly being added and needs to be analyzed quickly.

For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf)or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).


by Arlyne at Sep 18, 2024, 02:40 AM

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Eileen
9 months ago
Not sure if online learning is the best choice here...
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Fernanda
9 months ago
Online learning makes sense with new data coming in!
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Nilsa
9 months ago
Wait, is patchwork learning even a thing?
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Lashaunda
10 months ago
I thought it was batch learning?
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Alpha
10 months ago
Definitely online learning!
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Magda
10 months ago
Patchwork learning sounds familiar, but I don't recall it being a standard term in our studies.
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Valentin
10 months ago
I remember practicing a question about this, and I think online learning was the answer because it adapts to new data continuously.
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Alona
10 months ago
I'm not entirely sure, but batch learning seems like it could fit too, since it processes data in chunks.
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Weldon
11 months ago
I think we might be looking for online learning here, especially since it deals with frequent new data.
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Sonia
11 months ago
Hmm, I'm a bit stumped on this one. The question is asking about the type of machine learning we'd use, but the options don't seem super clear to me. I'll have to review my notes on the different learning approaches and see if I can figure out which one fits best with the constraints mentioned. Hopefully I can narrow it down.
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Marcos
11 months ago
Okay, I've got this. With a large dataset and limited resources, we can't really do batch learning since that requires loading the entire dataset into memory. And "big data learning" isn't a real thing, so that's not the answer. That leaves online learning as the best option - it can handle new data as it comes in without needing to retrain on the full dataset each time. I'm confident that's the right approach here.
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Aja
11 months ago
This seems like a straightforward question about different machine learning approaches. I think the key is to identify the approach that can handle large datasets, limited resources, and frequent new data - that sounds like online learning to me.
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Quentin
11 months ago
Hmm, I'm a bit unsure about this one. I know there are different learning approaches like batch and online, but I'm not totally clear on the differences and which one would be best for the scenario described. I'll have to think this through carefully.
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Viola
11 months ago
This looks like a pretty straightforward configuration question for a Cisco Catalyst 9800 Series Wireless Controller. I think I can handle this one.
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Maryann
2 years ago
Online learning is the way to the future! Big Data is hungry, and it needs that constant feeding.
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Genevive
2 years ago
Exactly, with online learning, we can adapt quickly to new data.
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Shoshana
2 years ago
Batch learning can be too slow for that kind of environment.
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Augustine
2 years ago
Online learning is definitely the way to go!
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Levi
2 years ago
I agree, it's perfect for handling large datasets and frequent updates.
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Lorrie
2 years ago
I'm not sure, but I think A) Batch learning could also be a good option for large datasets.
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Otis
2 years ago
I agree with Margart, online learning is the way to go with limited resources.
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Carlene
2 years ago
D) Online learning. The real-time updates are crucial when you're working with a constantly changing dataset. No time for that batch stuff.
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Rosann
2 years ago
D) Online learning.
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Torie
2 years ago
B) Big Data learning.
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Latosha
2 years ago
A) Batch learning.
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Mariko
2 years ago
Online learning, for sure. Gotta keep up with that data flow, am I right? Batch learning is so 2010.
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Laurel
2 years ago
I prefer Patchwork learning. It's like a cozy quilt of knowledge, each patch a little bit of learning.
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Margart
2 years ago
I think the answer is D) Online learning.
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Barabara
2 years ago
D) Online learning. That's the way to go when you're dealing with big data and limited resources. Ain't got time for no batch processing!
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Giovanna
2 years ago
D) Online learning. That's the way to go when you're dealing with big data and limited resources. Ain't got time for no batch processing!
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Sanda
2 years ago
D) Online learning.
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Alona
2 years ago
B) Big Data learning.
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Linwood
2 years ago
D) Online learning. That's the way to go when you're dealing with big data and limited resources. Ain't got time for no batch processing!
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Gianna
2 years ago
A) Batch learning.
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Serina
2 years ago
A) Batch learning.
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