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質問 1：
The least squares optimization technique (The Method of Least Squares) is used in which algorithm?
A. Linear regression
B. Support Vector Machines
C. Naive Bayes classification
D. Logistic regression
正解：A
質問 2：
What are two key characteristics of cloud architecture that could benefit AI applications? (Choose two.)
A. support for common business oriented language (COBOL) applications
B. constant attention needed for maintenance and support of the cloud platform
C. hybrid clouds enable the deployment of distributed large neural networks
D. the hardware requirement can be scaled up as per the demand
E. capable of managing and handling dynamic workloads with automatic recovery from failures
正解：D,E
質問 3：
Which statement is true for naive Bayes?
A. Naive Bayes doesn't require any assumptions about the distribution of values associated with each class.
B. Naive Bayes can be used for regression.
C. Naive Bayes is a conditional probability model.
D. Let p(C1 | x) and p(C2 | x) be the conditional probabilities that x belongs to class C1 and C2 respectively, in a binary model, log p (C1 | x) - log p(C2 | x) > 0 results in predicting that x belongs to C2.
正解：C
質問 4：
Which situation would disqualify a machine learning system from being used for a particular use case?
A. The neural network for the model requires significantly more computing power than a logistic regression model.
B. Data for the machine learning model is available only as static CSV files.
C. Training and testing data for the model contain outliers.
D. The use case requires a 100% likelihood of making a correct/true prediction.
正解：A
質問 5：
Which is an example of a nominal scale data?
A. a variable bank account balance whose possible values are $5, $10, and $15
B. a variable temperature with a scale of values low, medium, and high
C. a variable industry with categorical values such as financial, engineering, and retail
D. a variable mood with a scale of values unhappy, ok, and happy
正解：A
The least squares optimization technique (The Method of Least Squares) is used in which algorithm?
A. Linear regression
B. Support Vector Machines
C. Naive Bayes classification
D. Logistic regression
正解：A
質問 2：
What are two key characteristics of cloud architecture that could benefit AI applications? (Choose two.)
A. support for common business oriented language (COBOL) applications
B. constant attention needed for maintenance and support of the cloud platform
C. hybrid clouds enable the deployment of distributed large neural networks
D. the hardware requirement can be scaled up as per the demand
E. capable of managing and handling dynamic workloads with automatic recovery from failures
正解：D,E
質問 3：
Which statement is true for naive Bayes?
A. Naive Bayes doesn't require any assumptions about the distribution of values associated with each class.
B. Naive Bayes can be used for regression.
C. Naive Bayes is a conditional probability model.
D. Let p(C1 | x) and p(C2 | x) be the conditional probabilities that x belongs to class C1 and C2 respectively, in a binary model, log p (C1 | x) - log p(C2 | x) > 0 results in predicting that x belongs to C2.
正解：C
質問 4：
Which situation would disqualify a machine learning system from being used for a particular use case?
A. The neural network for the model requires significantly more computing power than a logistic regression model.
B. Data for the machine learning model is available only as static CSV files.
C. Training and testing data for the model contain outliers.
D. The use case requires a 100% likelihood of making a correct/true prediction.
正解：A
質問 5：
Which is an example of a nominal scale data?
A. a variable bank account balance whose possible values are $5, $10, and $15
B. a variable temperature with a scale of values low, medium, and high
C. a variable industry with categorical values such as financial, engineering, and retail
D. a variable mood with a scale of values unhappy, ok, and happy
正解：A
Hoshino -
いやー本当にすげーわ。この問題集を購入したんだけど、三日前にC1000-059の試験に受けて、試験にある内容はほぼ問題集に出てて凄かった。合格しました。IBMさん、今後もお世話になります！