Preparing for the final
The final exam will run from 3:00 to 4:00 on Thursday, March 8.
The final exam will cover chapters 1 through 8 in the textbook. The exam will test your knowledge of key concepts in machine learning. I will pick several topics from the list below and ask you to write a short description of that concept to explain what it is for/and or what it does.
Here the list of questions you should be prepared to answer:
- What is regression?
- What is classification?
- What is a decision function?
- What is a confusion matrix?
- How does the one-vs-all strategy differ from one-vs-one strategy?
- What is Logistic regression?
- What is polynomial regression?
- How does regularization help prevent overfitting?
- What is Ridge regression?
- What does a support vector machine seek to optimize?
- How do you construct a random forest?
- How does PCA work?
- How does LLE work?
- How does the k-nearest neighbors classification model work?