Introduction to Machine Learning

Assignments

There will be 9 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.

• Homework 1: Background Material (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW1
• Homework 2: Decision Trees (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW2
• Homework 3: KNN, Perceptron, and Linear Regression (written)
  • Handout
  • Overleaf Link
  • Exit Poll: HW3
• Homework 4: Logistic Regression (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW4
• Homework 5: Neural Networks (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW5
• Homework 6: Generative Models (written)
  • Handout
  • Overleaf Link
  • Exit Poll: HW6
• Homework 6.5: Narwhal Networks (written)
  • Handout
  • Overleaf Link
  • Exit Poll: HW6
• Homework 7: Hidden Markov Models (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW7
• Homework 8: Reinforcement Learning (written / programming)
  • Handout
  • Overleaf Link
  • Exit Poll: HW8
• Homework 9: Learning Paradigms (written)
  • Handout
  • Overleaf Link
  • 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 1-7
  • Practice Problems
  • Practice Problems (Solutions)
  • Exit Poll: Exam 1
• Exam 2 (in-person): Lectures 8-17
  • Practice Problems
  • Practice Problems (Solutions)
  • Poll: Course Evaluation
• Exam 3 (in-person): Lectures 18-27
  • Practice Problems
  • Practice Problems (Solutions)