Get All Weeks Cloud Machine Learning Engineering and MLOps Quiz Answers
Week 01: Cloud Machine Learning Engineering and MLOps Quiz Answers
Quiz 01: Week 1 Quiz
Q1. What is a key difference between Data Science and ML Engineering?
- Models go to production in ML Engineering
- Model accuracy is most important for ML Engineering
- Models should be share on Kaggle in ML Engineering
Q2. Why is an advantage of using a widely used ML Platform?
- Maintainability
- Easy to hire talent
- Communication
Q3. What is an advantage of Flask for ML Engineering?
- Easy to create Microservices
- Has an admin interface
- Designed for building a Content Management Site
Q4. How can ML Engineering used?
- Building mobile apps
- Create working systems that deliver predictions
- Building web apps
Q5. What is Continuous Delivery?
- Code is always in a deployable state
- It is a database system
- It is an algorithm
Q6. What would be an example of an ML application?
- Automated License plate reader
- Mobile Photo Sharing app
- Blog
Q7. Why would a Microservice be valuable for ML?
- Single purpose
- The Microservice can turn into a mobile app
- It can make websites
Q8. What is an example of a Machine Learning Engineering platform?
- Google News
- AWS Sagemaker
- Google Analytics
Q9. What problems do Machine Learning platforms solve?
- Object Storage
- Training large models
- Block Storage
Q10. What advantage could a ML platform create for deployment?
- Create a new job, release manager
- Adds more human QA
- Deployment to scalable endpoints
Week 02: Cloud Machine Learning Engineering and MLOps Quiz Answers
Quiz : Week 2 Quiz
Q1. What is AutoML?
- A form of Machine Learning training that is fully automated
- A web service
- An API
Q2. What type of problem could you solve with Cloud AutoML?
- Websites
- AGI (Artificial General Intelligence)
- Computer Vision
Q3. Why would an organization want to use AutoML vs tuning Hyperparameters themselves?
- Better accuracy
- Increase the velocity of model deployment
- This is rarely done because humans must modify Hyperparemeters
Q4. What is Ludwig?
- A closed course AutoML system
- A toolbox for creating ML models without code
- An AutoML system that requires deep software skills
Q5. What is an advantage of AutoML?
- Human judgement to evaluate conclusion is removed
- Bad data is automatically fixed
- Train many models at the same time
Q6. How could AutoML help explainability of a model?
- They come with a staff of experts
- Accuracy is improved through complexity
- Automated Explainability tools
Q7. Where is a popular location designed to download pre-trained models?
- Tensorflow Hub
- Github
- Bitbucket
Q8. Which are examples of AutoML systems?
- Google Cloud AutoML Vision
- Azure ML Studio
- AWS Sagemaker AutoPilot
Q9. What is an example of a ML model deployment target for AutoML?
- Edge Device
- Mobile
- Database
Q10. What is an example of an AutoML solution by Apple?
- Create ML
- iOS
- OS X
Week 03: Cloud Machine Learning Engineering and MLOps Quiz Answers
Quiz : Week 3 Quiz
Q1. What is MLOps?
- Testing
- QA
- Combination of best practices of DevOps and Machine Learning
Q2. What advantage does an AI API offer?
- Free
- Leverage the expertise of experts
- Custom business logic
Q3. What is a use case for Edge ML?
- Desktop PC
- Low latency prediction
- Windows Server
Q4. What is an advantage of small edge inference?
- Includes AutoML
- Doing ML predictions on portable devices
- More powerful than GPU
Q5. What is a sentiment analysis API?
- A feature in a blog
- A feature in a mobile app
- Detects the emotion in text
Q6. What is an advantage of medical AI APIs?
- Free
- They only run on Mobile
- Can validate that correct prescription drugs are given
Q7. Why would a company shift resources from Data Science to MLOps
- They cannot hire Data Scientists
- Increase the models that make it to production
- They don’t care about model quality
Q8. What is one thing MLOps does?
- Enables Data Science and IT to work together
- Builds websites
- Builds mobile apps
Q9. Why would a company care about “Data Drift”?
- Data drift makes models more explainable
- Data Drift is helpful to model accuracy
- Model accuracy
Q10. Why would an MLOPs practitioner need to know Continuous Integration?
- The foundation of MLOps
- It is a classification algorithm
- It is a regression algorithm
