MLOps — Learn free · DataAI Nexus

Self-check

Questions 1–10 of 10

1. What does MLOps cover?
Question 1A. Only the monitoring of models already in productionB. The whole journey of a machine learning model, from the availability of raw data until the model is deployed in productionC. The provisioning of servers for data scientistsD. The security of training dataE. The design of dashboards for model results
2. Roughly what proportion of machine learning models are said never to reach production?
Question 2A. 10%B. 50%C. 75%D. 90%E. 99%
3. What vital role does CI/CD play in MLOps?
Question 3A. Moving models between the development and training areas again and again, and to production once the owner confirmsB. Replacing the need for model validationC. Generating training data automaticallyD. Choosing which algorithm to useE. Writing the problem definition
4. From which concept was MLOps extracted?
Question 4A. Data WarehousingB. WaterfallC. ITILD. Data MiningE. DevOps
5. Which of the following is NOT part of the Model Development phase of MLOps?
Question 5A. Problem DefinitionB. Data SelectionC. Smoke TestD. Data WranglingE. Model Validation
6. Which of the following is NOT listed under the Prediction Serving phase of MLOps?
Question 6A. Online InferenceB. Batch InferenceC. Streaming InferenceD. Embedded InferenceE. Data Drift
7. What does the Continuous Monitoring phase of MLOps watch for?
Question 7A. Data Drift, Concept Drift and Continuous DriftB. Server uptime and CPU usageC. Code coverage and unit test resultsD. User login failuresE. Storage costs
8. Which steps make up the Continuous Training phase of MLOps?
Question 8A. Build, Test and Deployment to ProductionB. Problem Definition and Data ExplorationC. Data Ingestion, Data Validation, Data Transformation, Model Training, Model Evaluation, Model Validation and Model RegistrationD. Smoke Test and ReleaseE. Online and Batch Inference
9. From where are the key phases of MLOps said to be taken?
Question 9A. The ISO software life cycle standardB. The Scrum guideC. A university textbook on statisticsD. Best practice on Databricks, Google and a few other placesE. The Hadoop documentation
10. MLOps is described as belonging to the same family as which other practices?
Question 10A. Waterfall and SpiralB. DevOps, DevSecOps and DataOpsC. OLTP and OLAPD. ACID and BaSEE. Partitioning and Sharding