MCQs

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Overall MCQs for Reference

1. Which best describes an API in machine learning?
   a. A database system
   b. A software intermediary allowing applications to communicate
   c. A hardware interface
   d. An operating system kernel
   Answer: balooba​
2. What is the primary benefit of providing ML models via APIs?
   a. Hiding the source code
   b. Enabling easy and scalable access to model predictions
   c. Increasing hardware usage
   d. Avoiding web security issues
   Answer: bmoesif+1​
3. Which HTTP method is commonly used to request predictions from an ML API?
   a. GET
   b. POST
   c. DELETE
   d. TRACE
   Answer: bmoesif+1​
4. When should you use a REST API over a GraphQL API for ML model access?
   a. When fewer endpoints are required
   b. For strict resource structure and stateless operations
   c. For only batch predictions
   d. For real-time socket streaming
   Answer: bstackoverflow+1​
5. What does endpoint refer to in an ML API context?
   a. The function’s return type
   b. The URL exposed by the API for specific functionality
   c. The ML model itself
   d. The operating system’s memory location
   Answer: balooba​
6. Which of the following is a common authentication method for ML APIs?
   a. API Keys
   b. BIOS password
   c. Cursor pointer
   d. USB security token only
   Answer: amoesif+1​
7. Standardization of endpoints in API-based ML deployment primarily improves:
   a. Hardware compatibility
   b. Developer usability and maintainability
   c. Compiler speed
   d. RAM allocation
   Answer: balooba+1​
8. Which of these is NOT a best practice when exposing ML models via API?
   a. Versioning your API
   b. Providing clear documentation
   c. Allowing unauthenticated access
   d. Using standardized request/response formats
   Answer: clearn.microsoft+1​
9. Which API response format is considered most universal for data exchange?
   a. TXT
   b. JSON
   c. EXE
   d. CSV
   Answer: bmoesif+1​
10. Why is input data validation critical in ML APIs?
    a. It speeds up the compiler
    b. It ensures correct model predictions and prevents errors
    c. It reduces code size
    d. It changes the ML model
    Answer: bmoesif​
11. Which scenario best fits batch prediction APIs in ML?
    a. Large datasets sent in a single API request for prediction
    b. Streaming predictions in real time
    c. Only returning model metadata
    d. Restricting access to public requests
    Answer: aalooba+1​
12. What is versioning in the context of ML APIs?
    a. Documenting response time
    b. Creating multiple endpoints for different model or API versions
    c. Encrypting all responses
    d. Changing default port numbers
    Answer: blearn.microsoft​
13. Which API would you use for advanced facial recognition in your ML app?
    a. Perspective API
    b. SkyBiometry
    c. Google Translate API
    d. TensorFlow Serving API
    Answer: bmoesif​
14. What is “swagger” commonly used for in ML API development?
    a. Model evaluation metric
    b. Interactive API documentation and testing
    c. Data encryption tool
    d. Frontend framework
    Answer: balooba​
15. Which HTTP status code denotes a successful ML API prediction request?
    a. 404
    b. 500
    c. 200
    d. 301
    Answer: cmoesif​
16. Why is asynchronous job handling useful in ML APIs?
    a. To modify API keys
    b. To handle long-running model predictions without blocking the client
    c. To prevent POST requests
    d. For hardware resets
    Answer: balooba+1​
17. What does CORS regulate in an ML API?
    a. Model training cycles
    b. Cross-Origin Resource Sharing (browser access rules)
    c. Core dumping
    d. Core frequency speed
    Answer: bstackoverflow+1​
18. Which is NOT a security best practice for ML APIs?
    a. Using HTTPS
    b. Allowing unrestricted IP access
    c. Input validation
    d. Using authentication tokens
    Answer: balooba+1​
19. What does the “payload” commonly refer to in ML APIs?
    a. The API endpoint name
    b. Data sent in the body of a request
    c. Server operating system
    d. RAM allocation for models
    Answer: bmoesif+1​
20. Which model deployment platform helps standardize ML API endpoints?
    a. Notepad++
    b. UbiOps
    c. MS Paint
    d. WinRAR
    Answer: bmoesif​
21. A POST request to an ML classification API typically includes:
    a. Only the model weights
    b. Input data for prediction
    c. Source code of the model
    d. Details of the frontend framework
    Answer: balooba+1​
22. The output of an ML prediction API is commonly:
    a. Encrypted database path
    b. Model’s predicted label or value
    c. Model architecture diagram
    d. Input feature list
    Answer: balooba+1​
23. Why is API request throttling sometimes needed in ML services?
    a. To allow unlimited access
    b. To prevent abuse and manage resource usage
    c. To speed up frontend refresh
    d. To compile source code
    Answer: bmoesif​
24. Which HTTP response would you expect for an unauthorized ML API request?
    a. 200
    b. 401
    c. 304
    d. 100
    Answer: balooba+1​
25. In API-based ML deployment, “latency” refers to:
    a. The total number of models
    b. Time taken to process a request and respond
    c. The size of the training dataset
    d. Number of features in the dataset
    Answer: bmoesif+1​
26. How do APIs support continuous model improvements in ML apps?
    a. By exposing static predictions only
    b. Allow new models to be deployed seamlessly without changing client code
    c. Requiring constant manual updates by users
    d. Using only GET methods
    Answer: balooba​
27. A commonly used protocol for ML API data exchange is:
    a. SMTP
    b. HTTP/HTTPS
    c. FTP
    d. UDP
    Answer: bmoesif+1​
28. A specialized ML API for text toxicity detection is:
    a. Roboflow
    b. Perspective API
    c. TensorFlow API
    d. ImageNet
    Answer: bmoesif​
29. Which API is suitable for deploying custom ML models?
    a. RESTful API
    b. SQL API
    c. Bluetooth API
    d. FTP API
    Answer: alearn.microsoft+1​
30. What’s a typical use case for a GET request in ML APIs?
    a. Sending training data
    b. Retrieving prediction results or model metadata
    c. Updating models
    d. Deleting endpoints
    Answer: balooba​
31. How do API keys enhance security for ML APIs?
    a. By hiding the server IP address
    b. By authenticating and controlling user access
    c. By preventing system boots
    d. By deleting data automatically
    Answer: balooba+1​
32. Why should an ML API use pagination?
    a. To encrypt responses
    b. To limit the amount of returned data per request for large datasets
    c. To create more endpoints
    d. To select models
    Answer: bstackoverflow​
33. An ML API most likely returns what data format for tabular predictions?
    a. MP3
    b. JSON
    c. PNG
    d. OBJ
    Answer: bmoesif+1​
34. Integrating error handling in ML APIs helps:
    a. Hide status messages
    b. Return clear messages for issues such as unsupported inputs
    c. Reduce code size
    d. Compile models faster
    Answer: balooba+1​
35. Which permission restriction can enhance ML API security?
    a. Rate limiting access
    b. Allowing all origins
    c. Disabling HTTPS
    d. Linking to third-party scripts freely
    Answer: amoesif+1​
36. Which scenario requires model input preprocessing within the API?
    a. Data is always preprocessed client-side
    b. Input data comes in unfixed formats needing normalization or encoding
    c. Model does not need input data
    d. Only weights are exchanged
    Answer: bmoesif​
37. Why is logging important for ML APIs?
    a. To increase download speeds
    b. For monitoring usage and diagnosing errors
    c. For compiling models
    d. For client-side speed
    Answer: balooba+1​
38. An API contract in ML refers to:
    a. A legal agreement between companies
    b. Defined request/response formats and behaviors
    c. Model training epochs
    d. Hardware resource measurement
    Answer: balooba​
39. Why would an ML API return a 429 status code?
    a. Wrong credential format
    b. Too many requests (rate limit exceeded)
    c. No internet connection
    d. Valid request processed
    Answer: bstackoverflow+1​
40. An ML model deployment pipeline often ends with:
    a. Model serialization
    b. Provisioning an API for prediction access
    c. Data encryption
    d. Hyperparameter tuning
    Answer: bmoesif+1​
41. When using a cloud ML API platform, which is NOT a typical task?
    a. Model uploading
    b. Model training in the API endpoint
    c. Endpoint configuration
    d. API key management
    Answer: balooba​
42. The term “statelessness” in ML APIs indicates that:
    a. Each API call is independent of previous requests
    b. Cookies are always required
    c. Model results are cached forever
    d. Data is stored in browser cache
    Answer: aalooba​
43. Why is API documentation crucial for ML APIs?
    a. To help developers understand how to interact with the API
    b. To obscure all endpoint names
    c. To encrypt all traffic by default
    d. To hide model details forever
    Answer: amoesif+1​
44. What advantage does using Docker bring to ML API deployment?
    a. Ensures consistent environment for model and API execution across platforms
    b. It speeds up GET requests
    c. Reduces need for data validation
    d. Disables HTTPS
    Answer: amoesif​
45. What is the main benefit of providing model versioning in the API path (e.g., /v1/model)?
    a. Prevents changes in other API endpoints
    b. Supports backward compatibility for clients using older models
    c. Optimizes data serialization
    d. Compiles source code faster
    Answer: blearn.microsoft+1​
46. A “health check” endpoint in an ML API is used to:
    a. Return server disk usage
    b. Indicate whether the API and model are working correctly
    c. Update API documentation
    d. Retrieve all training logs
    Answer: bmoesif​
47. Why should API input limit be set for ML endpoints?
    a. To avoid large payloads that may degrade service or cause timeouts
    b. To help in model training
    c. To increase input variety
    d. To ease frontend styling
    Answer: aalooba+1​
48. For ML APIs, what does “namespace” help define?
    a. API endpoint grouping for organization, e.g., /api/v1/images, /api/v1/text
    b. Training dataset structure
    c. The model’s RAM usage
    d. CPU core count
    Answer: aalooba​
49. The fastest way to expose a PyTorch or TensorFlow model as an API is via:
    a. WinZip
    b. FastAPI or Flask microservice
    c. Manual HTTP POST via email
    d. Browsing the dataset
    Answer: bmoesif+1​
50. Why is monitoring API latency crucial after deploying an ML model?
    a. To verify and improve the real-time responsiveness of predictions
    b. To increase RAM usage
    c. For frontend presentation only
    d. For security patching
    Answer: aalooba+1​

1. https://www.alooba.com/skills/concepts/systems-architecture-71/api-design-for-ml-models/
2. https://www.moesif.com/blog/technical/api-development/APIs-For-Machine-Learning/
3. https://stackoverflow.blog/2020/03/02/best-practices-for-rest-api-design/
4. https://learn.microsoft.com/en-us/azure/architecture/best-practices/api-design
5. https://futureskillsacademy.com/blog/top-machine-learning-mcqs-with-answers/
6. https://interviewkickstart.com/blogs/articles/machine-learning-mcqs-answers
7. https://www.geeksforgeeks.org/quizzes/machine-learning-quiz-questions-and-answers/
8. https://www.sanfoundry.com/1000-machine-learning-questions-answers/
9. https://aticleworld.com/rest-api-mcq/
10. https://diptisurvase.wordpress.com/wp-content/uploads/2022/09/ml-mcqs.pdf
11. https://365datascience.com/career-advice/job-interview-tips/machine-learning-interview-questions-and-answers/
12. https://www.scribd.com/document/513570416/ACFrOgCJFUigNteKuu50LJxpBGcbPjZqsROcKBB5PyM5KE-Q-oAs-YZJ3IADaoXffYVg95KJOlVhH3Y7i3EhDpSdahDSH67nvSoQ0jRcRPfnxznydI9KqW1NG5BlF4MYakTohHZdry6b99-9xv5H
13. https://www.interviewbit.com/machine-learning-mcq/
14. https://www.gravitee.io/blog/4-best-practices-for-integrating-ai-machine-learning-in-ap-is
15. https://trainings.internshala.com/blog/machine-learning-interview-questions-and-answers/
16. https://www.igmguru.com/blog/machine-learning-mcqs
17. https://www.gyansetu.in/blog/machine-learning-mcq-interview-preparation/
18. https://getsdeready.com/top-20-api-design-questions-for-system-design-interviews/
19. https://www.geeksforgeeks.org/machine-learning/machine-learning-interview-questions/
20. https://analyticstraininghub.com/mcq-for-machine-learning/