최신GIAC Machine Learning Engineer - GMLE무료샘플문제

A. Determining if there is a significant difference between the means of two groups

B. Classifying data into different categories

C. Visualizing the distribution of data

D. Reducing the dimensionality of the dataset

A. To describe the basic features of data

B. To visualize complex datasets

C. To classify data into different categories

D. To make predictions about a population based on a sample

A. Focus only on the most recent data and ignore the training set

B. Remove regularization and increase the number of training samples

C. Apply L2 regularization (Ridge), reduce the complexity of the model, and increase the size of the training dataset

D. Increase the number of features and training epochs

A. Creating Naive Bayes classifiers

B. Building decision trees

C. Calculating the posterior probability in classification tasks

D. Developing recommendation systems

A. Improving the computational efficiency of the model

B. Optimizing the model for better accuracy

C. Handling datasets where some classes are much more frequent than others

D. Reducing the dimensionality of the dataset

A. A model that performs well on training data but poorly on unseen data

B. The process of selecting the right hyperparameters

C. A model that performs well on both training and test data

D. A model that is too simple to capture the underlying pattern

A. A technique for training models on time-series data

B. A method for improving the accuracy of neural networks

C. The field that focuses on the interaction between computers and human language

D. The process of converting text data into numerical data

A. R-squared

B. Mean Absolute Error (MAE)

C. Root Mean Squared Error (RMSE)

D. Accuracy

A. The process of training a model with insufficient data

B. The use of too many features in the model

C. A condition where the model performs well on the training data but poorly on new, unseen data

D. A situation where the model is too simple to capture the complexity of the data

A. Representing hierarchical data

B. Displaying time-series data

C. Visualizing geographical data

D. Showing the relationship between two variables

A. Support Vector Machines

B. k-means

C. Decision Trees

D. Logistic Regression