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Databricks Certified Professional Data Scientist Exam - Topic 4 Question 47 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 47
Topic #: 4
[All Databricks Certified Professional Data Scientist Questions]

You have collected the 100's of parameters about the 1000's of websites e.g. daily hits, average time on the websites, number of unique visitors, number of returning visitors etc. Now you have find the most important parameters which can best describe a website, so which of the following technique you will use

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Suggested Answer: A

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Denna
3 months ago
Not sure if PCA is the best choice, what about clustering?
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Kayleigh
3 months ago
Totally agree, PCA helps in visualizing high-dimensional data effectively!
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Lorita
3 months ago
Wait, isn't PCA a bit complex for just finding important parameters?
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Ernestine
4 months ago
I think linear regression could work too, but PCA seems more fitting here.
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Nguyet
4 months ago
PCA is definitely the way to go for dimensionality reduction!
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Evangelina
4 months ago
I feel like linear regression might not be appropriate since we're not predicting a specific outcome, but I’m a bit confused about when to use logistic regression.
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Nickole
4 months ago
I practiced a similar question, and I believe PCA was highlighted as the best method for summarizing data. It makes sense for this scenario.
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Doyle
4 months ago
I'm not entirely sure, but I remember something about PCA being used for feature extraction. It seems relevant, but could clustering also work?
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Tegan
5 months ago
I think PCA is the right choice here since it helps reduce dimensionality and identify the most important features.
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Laurena
5 months ago
PCA is the way to go for this question. It's a powerful technique for dimensionality reduction that can help us identify the most important website parameters. I'll make sure to explain the key steps of the PCA algorithm and how it applies to this problem.
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Alpha
5 months ago
I'm a little confused by all the options presented here. What's the difference between linear regression and logistic regression? And how would clustering be used in this context? I'll need to review my notes to make sure I understand the pros and cons of each technique.
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Jacob
5 months ago
PCA is definitely the right choice here. It's perfect for identifying the key features that capture the most variance in a high-dimensional dataset like the website parameters we have. I feel confident I can explain the PCA approach well in my answer.
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Alethea
5 months ago
Hmm, I'm a bit unsure about this one. PCA, linear regression, and clustering all seem like they could be applicable. I'll need to think through the specifics of each method and how they might work for this problem.
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Veronika
5 months ago
This seems like a straightforward question on dimensionality reduction techniques. I think PCA is the way to go here since we're trying to find the most important parameters that can best describe the websites.
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Kassandra
5 months ago
Okay, let's see. We need to prevent VM1 and VM2 from accessing any other storage accounts, but still allow storage1 to be accessible from the internet. I think a private endpoint or a private link might be the way to go.
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Lucia
5 months ago
I'm not completely sure, but I feel like YAML could also be a default for some other CLI tools.
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Remedios
5 months ago
Okay, let me think this through. The question is asking for the hexadecimal reference for the text color, and the background is specified as black. So the answer must be the hexadecimal code for white.
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Lanie
5 months ago
Hmm, I think I remember learning about this in class, but I'm not totally sure. I'll have to think it through carefully.
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Tomoko
5 months ago
Triggering a PowerShell alert on the VM doesn't seem like the right approach here. I'm pretty sure we need to work in the Azure Security Center to set up the custom alert suppression rule.
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