ML System Design Simplified: 10 Beginner Questions Quiz

1. Understanding Components

   Which of the following is typically responsible for transforming raw data into a usable format in a machine learning system?

   1. A. Data preprocessing module
   2. B. Result visualization block
   3. C. Model inference controller
   4. D. Feedback loop engine
   5. E. Error logging thread

2. Selecting Storage Types

   When storing large volumes of unstructured text data for an ML project, which storage type is most suitable?

   1. A. Relational database
   2. B. Image cache
   3. C. Object storage
   4. D. Memory buffer
   5. E. Configuration file

3. Model Training Basics

   In a basic ML pipeline, what is the primary function of the training phase?

   1. A. Predicting outputs for new inputs
   2. B. Transforming visualizations
   3. C. Creating a feedback report
   4. D. Learning patterns from labeled data
   5. E. Deleting outdated files

4. Concept of Model Deployment

   If you want users to submit data to your model using an application interface, which component should handle this task?

   1. A. Data cleaning pipeline
   2. B. User endpoint API
   3. C. Randomization module
   4. D. Feature engineering block
   5. E. Plotting library

5. Monitoring Models

   Why is monitoring important after deploying a machine learning model to production?

   1. A. It helps track model accuracy and detect drift over time.
   2. B. It increases training dataset size.
   3. C. It reduces hardware requirements.
   4. D. It eliminates need for versions.
   5. E. It speeds up user registration.

6. Role of Feature Engineering

   In an ML system analyzing customer reviews, creating a 'review_length' feature from text is an example of what?

   1. A. Model validation
   2. B. Feature engineering
   3. C. Label encoding
   4. D. Output transformation
   5. E. Hyperperimeter tuning

7. Batch vs Real-Time Processing

   Which type of processing is ideal for making immediate predictions, such as classifying incoming SMS messages as spam or not?

   1. A. Batch processing
   2. B. Deferred analysis
   3. C. Real-time (online) processing
   4. D. Manual review
   5. E. Round-robbin method

8. Modular System Design

   What is a primary benefit of designing an ML system using a modular architecture?

   1. A. Easier to reuse and update parts independently
   2. B. Forces single programming language usage
   3. C. Reduces need for monitoring
   4. D. Speeds up internet connections
   5. E. Increases data duplication

9. Input Data Quality

   In a scenario where user-submitted images are sometimes blurry or poorly lit, which approach can improve the ML model's robustness?

   1. A. Automatically accept all images
   2. B. Use data augmentation during training
   3. C. Only use the largest images
   4. D. Disregard image quality
   5. E. Limit training to one image

10. Iterative Improvement

    After deploying an ML system, why is it important to collect feedback on prediction errors?

    1. A. To allow ongoing model improvements with new data
    2. B. To identify spelling mistakes in code
    3. C. To track server energy usage
    4. D. To increase product advertisements
    5. E. To reduce RAM capacity