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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
Suggested Answer: C
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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.
43 comments · newest first
DA
Darrin
11 months ago
Classification makes the most sense here, no doubt!
BE
Belen
11 months ago
I thought clustering was the way to go for this.
JA
Jacob
11 months ago
Wait, isn’t it more like regression?
AU
Audry
11 months ago
I agree, it’s all about categorizing the digits.
GU
Gussie
11 months ago
This is definitely classification!
RA
Raymon
12 months ago
I practiced a similar question, and I think classification is the best fit for recognizing handwritten digits.
JA
Janella
12 months ago
Clustering seems off too, since we’re not grouping similar items but rather categorizing them into distinct classes.
JE
Jeniffer
12 months ago
I'm not entirely sure, but I remember something about regression being used for predicting values, so that doesn't seem right here.
NA
Naomi
1 year ago
I think this might be classification since we're trying to identify specific digits from the images.
JO
Joseph
1 year ago
Okay, let's see. The question says the machine learning is used to "recognize" the digits, which makes me think it's a classification task. I'll go with option C.
TR
Tresa
1 year ago
Hmm, I'm a bit unsure here. Classifying digits could also be considered a regression problem, since we're trying to map the input image to a numerical output. I'll have to think this through carefully.
BL
Blair
1 year ago
This seems like a straightforward classification problem to me. The machine learning model is trying to classify the handwritten digits, so I'll go with option C.
KE
Kenny
1 year ago
I'm a little confused by this question. Reinforcement learning, regression, and clustering all seem like possible answers. I'll have to review my notes on the different machine learning techniques to decide.
SH
Sherron
1 year ago
Hmm, I'm a bit confused by the details here. I'll need to re-read the question and really understand the relationship between the purchase order, sales order, and intercompany project. Let me think this through step-by-step.
EL
Elouise
1 year ago
I remember we talked about capitation models in class, but I'm not 100% sure which one this is.
JA
Jamey
1 year ago
I'm a bit confused on this one. I know the extract process is important, but the other two options have me stumped. I'll have to make an educated guess and hope for the best.
CH
Charlena
1 year ago
Hmm, I'm not sure about this one. The question is a bit confusing. I'll need to think it through carefully.
WE
Wendell
2 years ago
Hey, at least it's not D) Clustering. That would be a real mess, trying to group handwritten digits together!
TA
Tandra
2 years ago
C) Classification
BU
Buffy
2 years ago
C) Classification
RE
Reynalda
2 years ago
B) Regression
JO
Jonell
2 years ago
A) Reinforcement learning
SU
Suzan
2 years ago
Recognizing digits, huh? Sounds like a job for my trusty neural network. I bet C) Classification is the way to go.
MI
Mitsue
2 years ago
I would go with C) Classification as well. It seems like the most suitable option for recognizing handwritten numbers.
KA
Katina
2 years ago
Yeah, I agree. Classification is definitely the way to go for this scenario.
MI
Minna
2 years ago
I think you're right, C) Classification is the best choice for recognizing digits.
BA
Barney
2 years ago
It makes sense, since we're trying to classify the scanned handwritten numbers into specific digits.
SA
Sarah
2 years ago
Yeah, I agree. Classification is typically used for categorizing data into different classes.
CA
Casandra
2 years ago
I think you're right, C) Classification seems like the best fit for recognizing digits.
GL
Glendora
2 years 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.
MA
Maile
2 years ago
Yeah, I agree. We're categorizing the digits into different classes, so it's definitely classification.
DO
Dorinda
2 years ago
I think you're right, C) Classification makes more sense for recognizing digits.
YU
Yuonne
2 years ago
I would go with C) Classification too, as it involves categorizing data into different classes.
TA
Tasia
2 years ago
I agree with Wilburn, because it's about recognizing specific categories.
SH
Shawnta
2 years ago
Recognizing digits from a handwritten scan? Definitely sounds like a classification problem to me.
GU
Gussie
2 years ago
This looks like a classic case of image classification using machine learning. I'd say the correct answer is C) Classification.
WI
Willard
2 years ago
Yeah, C) Classification seems like the most fitting option for this scenario.
AN
Antonio
2 years ago
I would go with C) Classification as well, since it's about recognizing specific patterns.
LA
Laurel
2 years ago
I think it's more about categorizing the digits, so C) Classification makes sense.
HA
Haley
2 years ago
Yeah, I think so too. C) Classification makes the most sense in this scenario.
BU
Buddy
2 years ago
I agree, it's definitely image classification. C) Classification is the right choice.
AD
Adell
2 years ago
I agree, it's definitely image classification. C) Classification is the right choice.
WI
Wilburn
2 years ago
I think it's C) Classification.