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DATA SCIENCE FOUNDATIONS FUNDAMENTALS QUESTIONS AND ANSWERS -13

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DATA SCIENCE FOUNDATIONS FUNDAMENTALS QUESTIONS AND ANSWERS -13

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DATA SCIENCE FOUNDATIONS FUNDAMENTALS QUESTIONS
AND ANSWERS #13

Which two methods are common algorithms for classifying new cases into existing
categories? - correct answer K-means and k-nearest neighbours

Data science methods can contribute to business intelligence by which tasks? - correct
answer All these answers

According to Drew Conway data science Venn diagram, what elements make up data
science? - correct answer hacking/programming, maths/statistics and other domain
expertise

People frequently ask whether they should learn python or r to do data science. What is
the answer that this video gives to this question? - correct answer A professional data
scientist should be comfortable with both Python and R, as well as several other.....
Science

While anomaly detection is normally associated with negative outcomes like fraud or
machine failure, it is more flexible than that. Which is the following is a positive outcome
in anomaly detection? - correct answer Identifying new markets with potential value

What is application programming interface (API)? - correct answer API routes the data,
translates it, and prepares it for use

What are artificial nerual networks modeled after? - correct answer neurons that are
inside a biological brain

Like general "software-as-a-service" or "saas," what is one of the major attractions of
"machine-learning-as-a-service" or "mlaas"? - correct answer You don't need to own or
maintain hardware, which can be flexibly allocated to your project

Which is a major goal of dimensionality reduction? - correct answer reducing noise in
the data

What is an advantage of in-house data for data science projects? - correct answer
Certain restrictions on data usage may not apply

Which is a common application of cluster analysis? - correct answer Audience
segmentation

How do decision trees provide rules for decision-making? - correct answer Decision
trees explicitly define binary decisions at each step in the data to reach the outcome
these decisions can then be used in other contexts

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