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Databricks Exam Databricks Certified Professional Data Scientist Topic 3 Question 56 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 56
Topic #: 3
[All Databricks Certified Professional Data Scientist Questions]

Which is an example of supervised learning?

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Suggested Answer: B

by Kerry at Apr 13, 2024, 02:36 AM

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Clarence
2 months ago
SVM? More like 'Super Versatile Machine'! It can do all sorts of cool stuff, like classifying proteins and recognizing handwritten characters. Who needs a human when you've got an SVM, am I right?
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Mike
16 days ago
It's amazing how SVMs can be applied to so many different fields, from text categorization to medical science.
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Amie
21 days ago
Yeah, SVMs are like the Swiss Army knife of machine learning algorithms.
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Jamey
24 days ago
I agree, SVMs are really versatile and can be used for a wide range of tasks.
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Laurene
2 months ago
SVM stands for Support Vector Machines, and it's a powerful supervised learning algorithm that can handle complex, high-dimensional data. It's a great choice for this question.
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Billy
1 months ago
SVMs are really versatile and can be used in many different applications
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Ilene
1 months ago
Yes, SVM is an example of supervised learning
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Wilburn
1 months ago
I think the answer is E) SVM
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Quentin
2 months ago
PCA and k-means are both unsupervised learning techniques, so they wouldn't be examples of supervised learning. SVD and EM are also not supervised learning.
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Erinn
26 days ago
Classification of images can also be performed using SVMs. Experimental results show that SVMs achieve significantly higher search accuracy than traditional query refinement schemes after just three to four rounds of relevance feedback.
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Gregoria
27 days ago
SVMs are helpful in text and hypertext categorization as their application can significantly reduce the need for labeled training instances.
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Latia
2 months ago
E) SVM
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Gilma
2 months ago
I think SVM is the correct answer here. It's a supervised learning algorithm that's used for classification and regression tasks.
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Temeka
20 days ago
Yes, SVMs are great for classifying proteins and achieving high accuracy.
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Geraldine
25 days ago
I didn't know SVMs could be used in medical science, that's really interesting.
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Tonja
1 months ago
I agree, SVMs are really versatile and can be used in various real world applications.
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Shantay
2 months ago
SVM is indeed the correct answer. It's a powerful algorithm for supervised learning.
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Janna
3 months ago
I think SVM is a powerful tool for supervised learning tasks, especially in medical science.
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Jesse
3 months ago
I agree with Karan, SVM can be used for text categorization and image classification.
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Karan
3 months ago
E) SVM is an example of supervised learning.
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