Logistics

• Lecturer: Evgeniya Korneva
• Pre-recorder video lectures: see group chat.
• Live practical sessions: Wednesdays & Fridays 19:00 Moscow time. Recordings are uploaded afterwards.
• Office hours: upon request

Useful Resources

Linear Algebra

• (course) Topics in Linear Algebra: lecture notes + quizes.
• (Youtube playlist) Linear Algebra for Engineers: a series of videos covering the most important concepts.
• (lecture notes) Linear Algebra in 25 Lectures (UC Davis)
• (book) Introduction to Applied Linear Algebra
• (book) Deep Learning - Part I

Calculus

• (Youtube playlist) Essence of Calculus
• (lecture notes) Introduction to Differential Calculus [pdf]
• (lecture notes) First Semester Calculus [pdf]

General

• (book) Mathematics for Machine Learning

LaTeX

• Learn LaTeX in 30 minutes – an Overleaf guide
• A series of great YouTube tutorials:
  • part 1: intro and overview of the very basics;
  • part 2: tables, figures, theorems and more;
  • part 3: writing a thesis with LaTeX.
• Detexify - draw a symbol you are looking for, and this web will give you its latex representation.

Graded assignments

• Graded assignmnet 4 [pdf][LaTeX template][submission form]
  • Deadline: Monday, October 21, 23:59 Moscow time
• Graded assignmnet 3 [pdf][notebook (task 2)][LaTeX template][submission form]
  • Deadline: Sunday, October 6, 23:59 Moscow time
• Graded assignment 2 [notebook][submission form]
  • Deadline: Sunday, September 29, 23:59 Moscow time
• Graded assignment 1 [pdf] [LaTex template][submission form]
  • Deadline: Friday, September 20, 18:59 Moscow time

Agenda

1. Wednesday, Sept 4: Introduction, Vectors and Distances

• Welcome quiz [google form]
• Vectors - Pyhton practice:
  • Color vectors [notebook][solutions]
  • Word vectors [notebook][solutions]
• Homework:
  • watch lectures 1 & 2 (see chat);
  • lecture 1 quiz [google form] (not graded).
• Getting familiar with LaTeX:
  • create an Overleaf account;
  • check out some of the tutorials (e.g., mentioned above);
  • practice: recreate the formulas you see (try not to look at the source first!) [link].

2. Friday, Sept 6: Hyperplanes

• Quiz review
• Linear classifier [notebook][solutions]

3. Wednesday, Sept 11: Vector Spaces

• Review lecture 2
• Gram-Schmidt process [notebook][solutions]
• Homework:
  • Quiz lectures 1 - 3 [google form]

4. Friday, Sept 13: Systems of Linear Equations

• Quiz review
• Method of least squares
  • Python practice [notebook]
• Homework
  • watch lecture 4
  • graded assignment 1 (deadline Wednesday, September 18, before the class)

5. Wednesday, Sept 18: Least Squares (part 2)

• Method of least squares continued
• Homework:
  • Quiz: [google form]

6. Friday, Sept 20: Matrix decompositions

• Review quiz lectuures 1-4
• LU, QR and Eigendecompositions
• Homework:
  • graded assignment 2 (deadline Sunday, September 29, 23:59 Moscow time)

7. Wednesday, Sept 25: PCA

• PCA
• Homework:
  • Python practice [notebook][solutions]
  • watch lecture 5

8. Friday, Sept 27: SVD

• Review PCA notebook
• SVD
• Homework:
  • graded assignment 3 (deadline Sunday, October 6, 23:59 Moscow time)
  • SVD Python practice [notebook]
  • watch lecture 6
    • Quiz: [google form]

9. Wednesday, Oct 2: Optimizing a function 1

• Univariate functions

10. Wednesday, Oct 9: Optimizing a function 2

• Multivariate functions

11. Friday, Oct 11: Optimizing a function 3

• Matrix calculus
• Homework:
  • graded assignment 4 (deadline Monday, October 21, 23:59 Moscow time)