machine learning with python ibm coursera quiz answers week 1

Graded Quiz: Intro to Machine Learning

1. In a dataset, what do the columns represent?

  • Variable Type
  • Observations
  • Features
  • Independent Variables

2. What is a major benefit of unsupervised learning over supervised learning?

  • Discover previously unknown information about the dataset.
  • Explore the relationship between features and the target.
  • Better evaluates the performance of a built model.
  • Being able to produce a prediction based on unlabelled data.

3. What’s the correct order for using a model?

  • Split the data into training and test sets, fit the model on the train set, evaluate model accuracy.
  • Split the data into the training and test sets, fit the model on the train set, clean the data, evaluate model accuracy.
  • Clean the data, fit the model on the entire dataset, split the data into training and test sets, evaluate model accuracy.
  • Clean the data, split the data into training and test sets, fit the model on the train set, evaluate model accuracy.

4. Which of the following is suitable for an unsupervised learning?

  • Predict house price based on location, house size, and number of rooms.
  • Segment customers into groups for discovering similar characteristics between them.
  • Examine the relationship between academic performance and level of in-class participation using observations that include a feature recording each student’s grade.
  • Classifying benign and malignant tumors using historical data on tumor shape, color, etc.

5. The main purpose of the NumPy library is to:

  • Achieve scientific computations.
  • Perform computations on arrays efficiently.
  • Construct machine learning models.
  • Visualize results in 2D and 3D plots.
     

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