A data scientist has a dataset of 10,000 rows and wants to evaluate a model. They split the data into 80% training and 20% validation. After training, they get a validation accuracy of 92%. They want a more reliable estimate of model performance. What should they do?

Train on the full dataset and report the training accuracy.

Increase the validation set to 30% and retrain.

Use 5-fold cross-validation and average the validation scores.

Use the same 80/20 split but change the random seed until accuracy improves.

What is a primary benefit of using MLflow to implement a training pipeline?

It tracks experiments, logs parameters, metrics, and artifacts, and helps manage the model lifecycle.

It automatically selects the best model architecture for your data.

It provides built-in hyperparameter optimization algorithms.

It guarantees that your model will achieve high accuracy on unseen data.

What does the 'k' in k-fold cross-validation represent?

The number of models in the ensemble

The number of hyperparameter combinations to test

The number of features in the dataset

The number of times the model is trained and evaluated

DatabricksCertified Machine Learning Associate

Domain 3Objective 3

Training Pipelines and Cross-Validation MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 6)

Part of the Section 3: Model Development domain, which makes up ~23% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~8–14 in this domain), expect 2–4 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

9concepts

Questions 26–29

26application · medium
A data scientist has a dataset of 10,000 rows and wants to evaluate a model. They split the data into 80% training and 20% validation. After training, they get a validation accuracy of 92%. They want a more reliable estimate of model performance. What should they do?
Select an answer first
27foundation · easy
What is a primary benefit of using MLflow to implement a training pipeline?
Select an answer first
28foundation · easy
If you perform a grid search with 5 hyperparameter combinations and use 4-fold cross-validation, how many models are trained in total?
Select an answer first
29foundation · easy
What does the 'k' in k-fold cross-validation represent?
Select an answer first

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Training Pipelines and Cross-Validation MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 6)

Questions 26–29

A data scientist has a dataset of 10,000 rows and wants to evaluate a model. They split the data into 80% training and 20% validation. After training, they get a validation accuracy of 92%. They want a more reliable estimate of model performance. What should they do?

What is a primary benefit of using MLflow to implement a training pipeline?

If you perform a grid search with 5 hyperparameter combinations and use 4-fold cross-validation, how many models are trained in total?

What does the 'k' in k-fold cross-validation represent?

Keep studying — Section 3: Model Development