CompTIA DY0-001 問題集

質問 1：
A data analyst wants to generate the most data using tables from a database. Which of the following is the best way to accomplish this objective?
A. LEFT OUTER JOIN
B. FULL OUTER JOIN
C. RIGHT OUTER JOIN
D. INNER JOIN
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 2：
An analyst is examining data from an array of temperature sensors and sees that one sensor consistently returns values that are much higher than the values from the other sensors. Which of the following terms best describes this type of error?
A. Synthetic
B. Systematic
C. Idiosyncratic
D. Heteroskedastic
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 3：
A data scientist is building a forecasting model for the price of copper. The only input in this model is the daily price of copper for the last ten years. Which of the following forecasting techniques is the most appropriate for the data scientist to use?
A. Autoregressive
B. Dynamic time warping
C. Moving average
D. Relative strength
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 4：
A data scientist has built a model that provides the likelihood of an error occurring in a factory. The historical accuracy of the model is 90%. At a specific factory, the model is reporting a likelihood score of 0.90. Which of the following explains a confidence score of 0.90?
A. Running this model 100 times within a factory it is expected the model will predict error 90 out of 100times the model is ran.
B. Running this model for all known factory issues, it is expected the model will identify 90 out of 100 known factory issues.
C. Running this model on 100 samples of factories, a certain model performance is expected for 90 out of the 100 samples.
D. Running this model 100 times on a factory, it is expected the model will predict 90 out of 100 factory errors.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 5：
A movie production company would like to find the actors appearing in its top movies using data from the tables below. The resulting data must show all movies in Table 1, enriched with actors listed in Table 2.

Which of the following query operations achieves the desired data set?
A. Perform a UNION between Table 1 using column Movie, and Table 2 using column Acted_In.
B. Perform an INNER JOIN between Table 1 using column Movie, and Table 2 using column Acted_In.
C. Perform a LEFT JOIN on Table 1 using column Movie, with Table 2 using column Acted_In.
D. Perform an INTERSECT between Table 1 using column Movie, and Table 2 using column Acted_In.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 6：
Which of the following image data augmentation techniques allows a data scientist to increase the size of a data set?
A. Scaling
B. Masking
C. Clipping
D. Cropping
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 7：
Which of the following layer sets includes the minimum three layers required to constitute an artificial neural network?
A. An input layer, a pooling layer, and an output layer
B. An input layer, a hidden layer, and an output layer
C. An input layer, a convolutional layer, and a hidden layer
D. An input layer, a dropout layer, and a hidden layer
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 8：
Which of the following is a key difference between KNN and k-means machine-learning techniques?
A. KNN is used for finding centroids, while k-means is used for finding nearest neighbors.
B. KNN performs better with longitudinal data sets, while k-means performs better with survey data sets.
C. KNN operates exclusively on continuous data, while k-means can work with both continuous and categorical data.
D. KNN is used for classification, while k-means is used for clustering.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 9：
Which of the following types of machine learning is a GPU most commonly used for?
A. Natural language processing
B. Tree-based
C. Deep learning/neural networks
D. Clustering
正解：C
解説: (Topexam メンバーにのみ表示されます)