リアルGIAC GMLE試験問題集には正解154問題と解答があります
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質問 # 30
Why is feature scaling important in machine learning?
Response:
- A. It makes the model training process faster
- B. It ensures that different features contribute equally to the model training
- C. It increases the number of features
- D. It helps in handling missing data
正解：B
質問 # 31
Which loss function is typically used for regression problems?
Response:
- A. Mean Squared Error (MSE)
- B. Hinge loss
- C. Kullback-Leibler divergence
- D. Cross-entropy loss
正解：A
質問 # 32
Which of the following is a supervised learning algorithm?
Response:
- A. Support Vector Machine (SVM)
- B. Principal Component Analysis (PCA)
- C. k-means clustering
- D. Autoencoders
正解：A
質問 # 33
Which algorithm is commonly used for anomaly detection in network traffic?
Response:
- A. Naive Bayes
- B. Linear Regression
- C. Decision Trees
- D. Autoencoders
正解：D
質問 # 34
In machine learning, what is 'feature engineering'?
Response:
- A. The process of choosing the right machine learning model
- B. The creation and optimization of new features from existing data
- C. The visualization of data features
- D. The selection of the best features for model training
正解：B
質問 # 35
Which of the following is a key step in data acquisition for machine learning models?
Response:
- A. Hyperparameter tuning
- B. Model evaluation
- C. Data cleaning
- D. Model deployment
正解：C
質問 # 36
What does the term 'epoch' refer to in the context of training a deep learning model?
Response:
- A. The initial phase of model training
- B. A single iteration over the entire dataset
- C. The final phase of model training
- D. The process of tuning hyperparameters
正解：B
質問 # 37
What is the scikit-learn library in Python best used for?
Response:
- A. Large-scale data processing
- B. High-performance computing
- C. Advanced data visualization
- D. Machine learning model development
正解：D
質問 # 38
Which two types of probabilities are essential in machine learning applications?
(Choose two)
Response:
- A. Marginal probability
- B. Uncertainty probability
- C. Absolute probability
- D. Conditional probability
正解：A、D
質問 # 39
Which activation function is typically used in the output layer of a neural network for binary classification?
Response:
- A. Sigmoid
- B. Softmax
- C. Tanh
- D. ReLU
正解：A
質問 # 40
In machine learning, what is a 'Support Vector Machine' (SVM) primarily used for?
Response:
- A. Dimensionality reduction and feature extraction
- B. Classification and regression tasks
- C. Time-series forecasting and sequence prediction
- D. Clustering and grouping similar data points
正解：B
質問 # 41
Which of the following are characteristics of hierarchical clustering?
(Choose two)
Response:
- A. It requires specifying the number of clusters in advance
- B. It scales better for large datasets compared to k-means
- C. It can be either agglomerative or divisive
- D. It creates a tree-like structure of nested clusters
正解：C、D
質問 # 42
Which functions are typically used for data manipulation in the Pandas library?
(Choose two)
Response:
- A. pd.DataFrame()
- B. plt.show()
- C. tf.keras.models()
- D. pd.merge()
正解：A、D
質問 # 43
What is the purpose of inferential statistics in machine learning?
Response:
- A. To describe the basic features of data
- B. To classify data into different categories
- C. To make predictions about a population based on a sample
- D. To visualize complex datasets
正解：C
質問 # 44
Which are common sources of data used in machine learning pipelines?
(Choose two)
Response:
- A. Web scraping
- B. Manual calculations
- C. Model ensembling
- D. APIs
正解：A、D
質問 # 45
You are using a CNN to classify images in a dataset. After several epochs of training, you notice that the model performs well on the training set but poorly on the validation set. This suggests overfitting.
What steps should you take to improve the generalization of the model?
Response:
- A. Train the model for more epochs and reduce the use of regularization
- B. Remove padding to simplify the architecture
- C. Implement dropout in the fully connected layers, apply data augmentation to increase the variability of the training data, and consider early stopping to prevent overfitting
- D. Reduce the size of the dataset and increase the number of convolutional layers
正解：C
質問 # 46
Which techniques are commonly used to optimize neural networks during training?
(Choose two)
Response:
- A. Softmax activation function
- B. Data augmentation
- C. Adam optimizer
- D. Stochastic Gradient Descent
正解：C、D
質問 # 47
What is the purpose of a p-value in hypothesis testing?
Response:
- A. To determine the probability of observing the data given that the null hypothesis is true
- B. To test for multicollinearity
- C. To measure the correlation between variables
- D. To calculate the mean of a dataset
正解：A
質問 # 48
Which of the following are common applications of Bayes' Theorem in machine learning?
(Choose two)
Response:
- A. Building decision trees
- B. Creating Naive Bayes classifiers
- C. Calculating the posterior probability in classification tasks
- D. Developing recommendation systems
正解：B、C
質問 # 49
What role does 'dropout' play in training deep neural networks?
Response:
- A. It accelerates the training process
- B. It helps prevent overfitting by randomly dropping units during training
- C. It introduces non-linearity into the model
- D. It increases the accuracy of the model on the training data
正解：B
質問 # 50
What is the primary use of 'k-fold cross-validation' in machine learning?
Response:
- A. To optimize the hyperparameters of the model
- B. To assess the model's performance on different subsets of the data
- C. To increase the size of the training dataset
- D. To select the most important features of the dataset
正解：B
質問 # 51
What role does 'batch size' play in training neural networks?
Response:
- A. It specifies the number of training examples used in one iteration
- B. It sets the total number of training iterations
- C. It determines the maximum number of features used in the model
- D. It adjusts the learning rate of the model
正解：A
質問 # 52
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