supervised machine learning regression and classification week 1 answers

Practice quiz: Supervised vs unsupervised learning

1. Which are the two common types of supervised learning? (Choose two)

  • Classification
  • Clustering
  • Regression

2. Which of these is a type of unsupervised learning?

  • Regression
  • Clustering
  • Classification

Practice quiz: Regression

3. For linear regression, the model is fw,b(x)=wx+b.

Which of the following are the inputs, or features, that are fed into the model and with which the model is expected to make a prediction?

  • and .
  • m
  • x (Correct Answer)

4. For linear regression, if you find parameters w and b so that J(w, b) is very close to zero, what can you conclude?

  • The selected values of the parameters and because the algorithm to fit the training set really well.
  • This is never possible — there must be a bug in the code.
  • The selected values of the parameters and cause the algorithm to fit the training set really poorly.

Practice quiz: Train the model with gradient descent

5. Gradient descent is an algorithm for finding values of parameters w and b that minimize the cost function J.

When ∂j(w,b)/∂w is a negative number (less than zero), what happens to w after one update step?

  • decreases
  • It is not possible to tell if will increase or decrease.
  • increases.
  • stays the same

6. For linear regression, what is the update step for parameter b?

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