GNRS 558 COMPREHENSIVE TEST BANK 2026
VERIFIED QUESTIONS AND SOLUTIONS STUDY
GUIDE
▶ Which of the following is NOT a use case for natural language
processing?
A. Public opinion analysis
B. Machine translation
C. Text classification
D. Image recognition - Answer: D
▶ Which of the following statements about different optimizers is false?
A. RMSprop solves the problem of the Adagrad optimizer ending too early.
B. Compared with RMSprop, Adagrad is more sensitive to gradient
changes.
C. Both Adagrad and RMSprop can set adaptive learning rate for
parameters.
D. Adam requires bias correction for initial iterations. - Answer: B
▶ Which of the following is NOT an Al deep learning framework?
A. TensorFlow
B. Scikit-learn
C. Pytorch
D. Caffe - Answer: B
▶ Which of the following statements is true about classification models and
regression models in machine learning?
A. For regression problems, the output variables are discrete values. For
classification problems, the output variables are continuous.
B. The most commonly used indicators for evaluating regression and
classification problems are the accuracy and the recall rate.
C. Overfitting may occur in both regression and classification problems.
D. Logistic regression is a typical regression model. - Answer: C
▶ Which of the following are used in TensorFlow to describe the
computation process?
A. Parameter
VERIFIED QUESTIONS AND SOLUTIONS STUDY
GUIDE
▶ Which of the following is NOT a use case for natural language
processing?
A. Public opinion analysis
B. Machine translation
C. Text classification
D. Image recognition - Answer: D
▶ Which of the following statements about different optimizers is false?
A. RMSprop solves the problem of the Adagrad optimizer ending too early.
B. Compared with RMSprop, Adagrad is more sensitive to gradient
changes.
C. Both Adagrad and RMSprop can set adaptive learning rate for
parameters.
D. Adam requires bias correction for initial iterations. - Answer: B
▶ Which of the following is NOT an Al deep learning framework?
A. TensorFlow
B. Scikit-learn
C. Pytorch
D. Caffe - Answer: B
▶ Which of the following statements is true about classification models and
regression models in machine learning?
A. For regression problems, the output variables are discrete values. For
classification problems, the output variables are continuous.
B. The most commonly used indicators for evaluating regression and
classification problems are the accuracy and the recall rate.
C. Overfitting may occur in both regression and classification problems.
D. Logistic regression is a typical regression model. - Answer: C
▶ Which of the following are used in TensorFlow to describe the
computation process?
A. Parameter
