Introduction to Machine Learning

Assignments

There will be 8 homework assignments during the semester in addition to the exams. The assignments will consist of both theoretical and programming problems. Homework assignments will be released via a Piazza announcement explaining where to find the handout, starter code, LaTeX template, etc.

The links to the Homework Handouts and Homework Exit Polls will be provided below. For Java and C++ users, please use these versions of the linear algebra libraries: Linear Algebra Libraries Handout

• Homework 1: Background Material (written / programming)
  • Handout
  • Exit Poll: HW1
• Homework 2: Decision Trees (written / programming)
  • Handout
  • Homework Groups: HW2
  • Exit Poll: HW2
• Homework 3: KNN, Perceptron, and Linear Regression (written)
  • Handout
  • Homework Groups: HW3
  • Exit Poll: HW3
• Homework 4: Logistic Regression (written / programming)
  • Handout
  • Homework Groups: HW4
  • Exit Poll: HW4
• Homework 5: Neural Networks (written / programming)
  • Handout
  • Homework Groups: HW5
  • Exit Poll: HW5
• Homework 6: Generative Models (written)
  • Handout
  • Homework Groups: HW6
  • Exit Poll: HW6
• Homework 7: Hidden Markov Models (written / programming)
  • Handout
  • Homework Groups: HW7
  • Exit Poll: HW7
• Homework 8: Reinforcement Learning (written / programming)
  • Handout
  • Homework Groups: HW8
  • Exit Poll: HW8
• Homework 9: Learning Paradigms (written)
  • Handout
  • Colab
  • Homework Groups: HW9
  • Exit Poll: HW9

Tentative release dates and due dates are listed on the Schedule page.

Exams

There will be three exams. The links to the Mock Exams, Practice Problems, and Exam Exit Polls will be provided below.

• Exam 1 (in-person): Lectures 1-8
  • Mock Exam 1
  • Practice Problems
  • Practice Problems (Solutions)
• Exam 2 (in-person): Lectures 9-17
  • Mock Exam 2
  • Practice Problems
  • Practice Problems (Solutions)
• Exam 3 (in-person): Lectures 18-26
  • Practice Problems
  • Practice Problems (Solutions)