2. Graded Quiz: Introduction to Machine Learning

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

• Features

• Independent Variables

• Variable Type

• Observations

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

• Being able to produce a prediction based on unlabelled data.

• Better evaluates the performance of a built model.

• Discover previously unknown information about the dataset.

• Explore the relationship between features and the target.

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

• 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, split the data into training and test sets, fit the model on the train set, evaluate model accuracy.

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

• Split the data into training and test sets, fit the model on the train set, evaluate model accuracy.

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

• • • Examine the relationship between academic performance and level of in-class participation using observations that include a feature recording each student’s grade.

    • Predict house price based on location, house size, and number of rooms.

    • Segment customers into groups for discovering similar characteristics between them.

    • Classifying benign and malignant tumors using historical data on tumor shape, color, etc.

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

• Construct machine learning models.

• Achieve scientific computations.

• Visualize results in 2D and 3D plots.

• Perform computations on arrays efficiently.