Methods of Mathematical Analysis

Summer Semester 2017

Lecturer: Clayton Greenberg

The new lecture hall is E1.3 HS002 (confirmed).

Exercises 1-5 and Solutions 1-5 have been emailed to all enrolled students.

Lecture slides are available in the Google Calendar description.

This course derives the most relevant results in calculus, mathematical logic, and linear algebra and applies those to some machine learning / natural language processing tasks.  Material will be presented at a level aimed as a gentle reintroduction to topics that may not have been used in recent studies.  However, students will be expected to participate actively in class and complete regular take-home exercises, in order to achieve operational competency by the end of the semester.

If you plan to take this course, please introduce yourself to me by email before the first course meeting on April 19.  In this email, I would like for you to self-evaluate your competency in linear algebra, calculus, and mathematical logic (including proofs).

Suitable for: LST / LCT / Computer Science / CuK

Meetings:  Wednesdays 12-14 c.t. beginning April 19, E1.3 HS002

Grading: written exam 100%

Exam qualification: must obtain 50 points on written exercises

In email related to this course: please use the subject tag [MoMA]

Literature (available at the UdS Informatics Library):

Eccles, P. J. (1997). An Introduction to Mathematical Reasoning: numbers, sets and functions. Cambridge University Press.

Lay, D. (2005). Linear Algebra and Its Applications, 3rd Updated Edition. Addison Wesley.

Stewart, J. (2002). Calculus: Early Transcendentals, 5th Edition. Brooks Cole.