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問題 #1

A market research team has ratings from patients who have a chronic disease, on several functional, physical, emotional, and professional needs that stay unmet with the current therapy. The dataset also captures ratings on how the disease affects their day-to-day activities.
A pharmaceutical company is introducing a new therapy to cure the disease and would like to design their marketing campaign such that different groups of patients are targeted with different ads. These groups should ideally consist of patients with similar unmet needs.
Which of the following algorithms should the market research team use to obtain these groups of patients?

A. k-nearest neighbors
B. Naive-Bayes
C. Logistic regression
D. k-means clustering

問題 #2

An organization sells house security cameras and has asked their data scientists to implement a model to detect human feces, as distinguished from animals, so they can alert th customers only when a human gets close to their house.
Which of the following algorithms is an appropriate option with a correct reason?

A. Logistic regression, because this is a classification problem and our data is linearly separable.
B. Neural network model, because this is a classification problem with a large number of features.
C. k-means, because this is a clustering problem with a small number of features.
D. A decision tree algorithm, because the problem is a classification problem with a small number of features.

問題 #3

A data scientist is tasked to extract business intelligence from primary data captured from the public. Which of the following is the most important aspect that the scientist cannot forget to include?

A. Cybersecurity
B. Data security
C. Cyberprotection
D. Data privacy

問題 #4

Which of the following best describes distributed artificial intelligence?

A. It relies on a distributed system that performs robust computations across a network of unreliable nodes.
B. It uses a centralized system to speak to decentralized nodes.
C. It does not require hyperparemeter tuning because the distributed nature accounts for the bias.
D. It intelligently pre-distributes the weight of starting a neural network.

問題 #5

Which two encoders can be used to transform categorical data into numerical features? (Select two.)

A. One-Hot Encoder
B. Median Encoder
C. Mean Encoder
D. Log Encoder
E. Count Encoder

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