the nuts and bolts of machine learning coursera week 1 quiz answers

Test your knowledge: Introduction to machine learning

1. Fill in the blank: Machine learning involves using algorithms and _____ to teach computer systems to analyze and discover patterns in data.

  • computer software
  • dynamic reports
  • decision-support systems
  • statistical models

2. A data professional using an unsupervised machine learning technique will ask a model to provide information based on a specified outcome.

  • True
  • False

3. Which approach to machine learning involves rewarding or punishing a computer’s behaviors?

  • Reinforcement learning
  • Supervised machine learning
  • Deep learning
  • Artificial intelligence

Test your knowledge: Categorical versus continuous data types and models

4. The weight of a surfboard is a continuous variable, whereas the number of surfboards currently at Bondi Beach is a discrete variable.

  • True
  • False

5. A data professional is working on a project that involves labeling thousands of books by their various book genres. What type of variable should they use when working with this dataset?

  • Categorical
  • Continuous
  • Discrete
  • Quantitative

Test your knowledge: Machine learning in everyday life

6. What term describes the subclass of machine learning algorithms that offers relevant suggestions to users?

  • Data models
  • Suggestion maps
  • Recommendation systems
  • Sensor techniques

7. Content-based systems are very effective at making recommendations across content types.

  • True
  • False

8. Fill in the blank: When several users actively like or dislike content by rating it or giving it a review, this enables _____ filtering.

  • crowdsourced
  • merit-based
  • preferential
  • collaborative

Shuffle Q/A 1

Test your knowledge: Ethics in machine learning

9. In recommendation systems, what term describes the phenomenon of more well-known items being recommended too frequently?

  • Fame factor
  • Trend partiality
  • Popularity bias
  • Non-objectivity

10. A data professional has just begun considering the intended purpose of a model and how harmful or significant its effects could be. Which PACE stage of model development does this scenario describe?

  • Analyze
  • Execute
  • Construct
  • Plan

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