C1000-144

Which technique is typically used to prevent overfitting in a decision tree classifier?A . Increasing the depth of the tree indefinitelyB . Using a linear kernel instead of a polynomial kernelC . Pruning the tree to remove non-significant branchesD . Applying PCA before training the classifierView AnswerAnswer: C

What is the benefit of feature scaling in model training?A . It increases the number of features for better accuracyB . It helps algorithms converge faster by normalizing feature magnitudesC . It decreases the transparency of the modelD . It is only useful for unsupervised learningView AnswerAnswer: B

What is the first step in aligning on user intents for an AI solution?A . Prototyping the solutionB . Identifying key stakeholdersC . Conducting a market analysisD . Documenting technical requirementsView AnswerAnswer: B

What is the primary use of the WHERE clause in an SQL query?A . To specify which columns to retrieveB . To limit the data that fits certain conditionsC . To identify the tables involved in the queryD . To denote the end of the SQL queryView AnswerAnswer: B

Which techniques ensure a model can explain its decisions and predictions?A . Implementing deep learning models exclusivelyB . Using highly non-linear models without any simplificationC . Integrating explanation frameworks like LIME or SHAPD . Minimizing the use of regularization techniquesView AnswerAnswer: C

In SQL, how would you extract the 'name' and 'age' columns from a table named 'customers'?A . SELECT name, age FROM customers;B . EXTRACT name, age FROM customers;C . GET name, age IN customers;D . PULL name, age OUT OF customers;View AnswerAnswer: A

Which approach would not be suitable for assessing model fairness?A . Analyzing confusion matrices for different subgroupsB . Using the same performance metric for all modelsC . Conducting audits on model decisionsD . Implementing external fairness monitoring toolsView AnswerAnswer: B

Which algorithm is most appropriate for non-linear classification problems?A . Linear regressionB . Logistic regressionC . Support Vector Machine with non-linear kernelsD . K-means clusteringView AnswerAnswer: C