C1000-154

Which statement describes bagging?A . Building models and using their output as features into a final model.B . Building models in parallel and aggregating their predictions to select the final prediction.C . Building models sequentially and evaluating the success of earlier models. It combines a set of weak learners into...

How can data splits be made reproducible in a machine learning experiment?A . By using a different random seed each time the data is splitB . By partitioning the data manuallyC . By using a consistent random seed when splitting the dataD . By splitting the data in a sequential...

In the context of avoiding underfitting and overfitting, what role does splitting the data into training, testing, and validation sets play?A . It ensures that the model is trained on the maximum amount of data possibleB . It allows for the model to be validated and tested on different subsets...

What is the key difference between batch processing and streaming in data processing?A . Batch processing involves real-time data processing, whereas streaming does not process dataB . Streaming is suitable for large, historical datasets, whereas batch processing is for real-time data analysisC . Batch processing processes data in large blocks...

Which of the following is NOT a type of data source commonly integrated with Cloud Pak for Data?A . Social media feedsB . Proprietary in-memory databasesC . Paper-based recordsD . Cloud storage servicesView AnswerAnswer: C

What is a key disadvantage of using Grid Search for hyperparameter tuning?A . It is too quick and may miss out on evaluating some hyperparametersB . It requires no prior knowledge of the hyperparametersC . It can be computationally expensive and time-consuming due to its exhaustive natureD . It is...

Which Python library is commonly used for data manipulation and analysis, and is available in Cloud Pak for Data?A . TensorFlowB . PyTorchC . PandasD . KerasView AnswerAnswer: C

Given the Confusion matrix below, which is the formula for specificity?A . TN/(TN + FP)B . TP/(FP + TP)C . TP/(FN + TP)D . (TP + TN)/(FN + FP + TN + TP)View AnswerAnswer: A

When selecting a small number of algorithms based on model requirements, what factor should you primarily consider?A . The popularity of the algorithm in recent academic papers.B . Compatibility of the algorithm with the data characteristics and the predictive task.C . The algorithm that requires the least amount of data...

In unsupervised learning, which algorithm is best suited for grouping customers based on their purchase history to target marketing efforts more effectively?A . Support Vector MachinesB . K-Means ClusteringC . Linear RegressionD . Decision TreesView AnswerAnswer: B