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Course Guidelines
About the course Prerequite Material References
Python
Jupyter Notebooks Python overview
Exercises
Before the semester start: Installation and exercise setup Week 1: Introduction to Python and libraries Week 2: Vector representations Week 3: Linear Algebra Week 4: Linear Transformations Week 5: Models and least squares Week 6: Assignment 1 - Gaze Estimation Week 7: Model selection and descriptive statistics Week 8: Filtering Week 9: Classification Week 10: Evaluation Week 11: Dimensionality reduction Week 12: Clustering and refresh on gradients Week 13: Neural Networks Week 14: Convolutional Neural Networks (CNN's)
Tutorials
Week 1: Data analysis, manipulation and plotting Week 2: Linear algebra Week 3: Transformations tutorial Week 4: Projection and Least Squares tutorial Week 7: Cross-validation and descriptive statistics tutorial Week 8: Filtering tutorial Week 11: Gradient Descent / Ascent
In-class Exercises
In-class 1 In-class 2 In-class 10 In-class 3 In-class 4 In-class 8
Explorer

Document

  • Overview
  • 1. Basic Linear Algebra in Python
  • 2. Pen and paper exercises

Content

  • Task 1
  • Task 2
  • Task 3

Pen and paper exercises

These exercises should be completed using only pen and paper. The goal is to test some of the basic linear algebra skills needed for proper understanding of the course material.

Task 1

Grasple - Exercise 1

Task 2

Grasple - Exercise 2

Task 3

Grasple - Exercise 3