Spring23 Final Exam Review Materials

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Below are review or practice materials available for the final exam, from previous semesters of 6.390 (6.036).

  • Note: some of the exams below covered topics that we did not cover. You are not responsible for these topics,including:

    • perceptrons (and margin maximization)
    • support vector machines (and hinge loss)
    • decision trees (and entropy)
    • recommender system (and collaborative filtering)

  • We encourage you to work the problems on your own first, and then later check your answers with the solutions or explanations.

  • You can find this semester's midterm exam and solutions here.

Recent Example Exams

Older Example Problems and Exams

Review Problems By Topic

A selection of past exam problems, grouped by topic:

  • ML process
  • Hypothesis class
  • Linear regression
  • Logistic regression
  • Gradient descent
  • Features
  • Nearest neighbors
  • NNs
  • CNNs
  • RNNs
  • MDPs
  • Reinforcement learning
  • Clustering

Problems, Solutions