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iSQI Exam CT-AI Topic 2 Question 6 Discussion

Actual exam question for iSQI's CT-AI exam
Question #: 6
Topic #: 2
[All CT-AI Questions]

A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?

SELECT ONE OPTION

Show Suggested Answer Hide Answer
Suggested Answer: C

Recognizing digits from a scan of handwritten numbers using machine learning is an example of classification. Here's a breakdown:

Classification: This type of machine learning involves categorizing input data into predefined classes. In this scenario, the input data (handwritten digits) are classified into one of the 10 digit classes (0-9).

Why Not Other Options:

Reinforcement Learning: This involves learning by interacting with an environment to achieve a goal, which does not fit the problem of recognizing digits.

Regression: This is used for predicting continuous values, not discrete categories like digit recognition.

Clustering: This involves grouping similar data points together without predefined classes, which is not the case here.


Contribute your Thoughts:

Wendell
4 months ago
Hey, at least it's not D) Clustering. That would be a real mess, trying to group handwritten digits together!
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Tandra
3 months ago
C) Classification
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Buffy
3 months ago
C) Classification
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Reynalda
3 months ago
B) Regression
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Jonell
3 months ago
A) Reinforcement learning
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Suzan
4 months ago
Recognizing digits, huh? Sounds like a job for my trusty neural network. I bet C) Classification is the way to go.
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Mitsue
2 months ago
I would go with C) Classification as well. It seems like the most suitable option for recognizing handwritten numbers.
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Katina
2 months ago
Yeah, I agree. Classification is definitely the way to go for this scenario.
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Minna
2 months ago
I think you're right, C) Classification is the best choice for recognizing digits.
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Barney
3 months ago
It makes sense, since we're trying to classify the scanned handwritten numbers into specific digits.
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Sarah
3 months ago
Yeah, I agree. Classification is typically used for categorizing data into different classes.
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Casandra
3 months ago
I think you're right, C) Classification seems like the best fit for recognizing digits.
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Glendora
4 months ago
Hmm, I'm not sure if it's B) Regression, since we're not trying to predict a continuous value. C) Classification seems more appropriate here.
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Maile
3 months ago
Yeah, I agree. We're categorizing the digits into different classes, so it's definitely classification.
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Dorinda
3 months ago
I think you're right, C) Classification makes more sense for recognizing digits.
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Yuonne
4 months ago
I would go with C) Classification too, as it involves categorizing data into different classes.
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Tasia
4 months ago
I agree with Wilburn, because it's about recognizing specific categories.
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Shawnta
4 months ago
Recognizing digits from a handwritten scan? Definitely sounds like a classification problem to me.
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Gussie
4 months ago
This looks like a classic case of image classification using machine learning. I'd say the correct answer is C) Classification.
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Willard
3 months ago
Yeah, C) Classification seems like the most fitting option for this scenario.
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Antonio
3 months ago
I would go with C) Classification as well, since it's about recognizing specific patterns.
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Laurel
3 months ago
I think it's more about categorizing the digits, so C) Classification makes sense.
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Haley
3 months ago
Yeah, I think so too. C) Classification makes the most sense in this scenario.
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Buddy
4 months ago
I agree, it's definitely image classification. C) Classification is the right choice.
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Adell
4 months ago
I agree, it's definitely image classification. C) Classification is the right choice.
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Wilburn
4 months ago
I think it's C) Classification.
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