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
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
