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10-607: Computational Foundations for Machine Learning

Instrutor: Bryan Wilder ([email protected])

TAs:
Naman Choudhary ([email protected])
Kunal Kapoor ([email protected])
Julia Liu ([email protected])

Office hours: see schedule in Canvas

Syllabus

Logistics

Questions: Piazza
Assignment submission: Gradescope
Both of the above can be accessed through the course Canvas page.

Course Description

This course provides a place for students to practice the necessary computational background for further study in machine learning. Topics covered include computational complexity, analysis of algorithms, proof techniques, optimization, dynamic programming, recursion, and data structures. The course assumes some background in each of the above, but will review and give practice in each. (It does not provide from-scratch coverage of all of the above, which would be impossible in a course of this length.) Some coding will be required: the course will provide practice with translating the above computational concepts into concrete programs.

Course Schedule

Week Dates Topic Assignments
1 Mon: Oct 21 Class intro, propositional logic [Slides] [Reference on logic] [Reference on predicates]
1 Wed: Oct 23 Proof techniques: direct proof, proof by cases [Slides] [Reference]
1 Fri: Oct 25 Recitation Homework 1 due Sunday
2 Mon: Oct 28 Proof techniques: contradiction, contraposition [Slides] [Reference]
2 Wed: Oct 30 Proof techniques: induction [Slides] [Reference (2.3)]
2 Fri: Nov 1 Recitation Homework 2 due Sunday
3 Mon: Nov 4 Computational complexity [Slides] [Notes]
3 Wed: Nov 6 Quiz 1 + Computational complexity [Slides] [Reference (3.6)]
3 Fri: Nov 8 Recitation Homework 3 due Sunday
4 Mon: Nov 11 Algorithms: recursion [Slides] [Reference (2.6-7)]
4 Wed: Nov 13 Algorithms: dynamic programming [Slides] [Notes]
4 Fri: Nov 15 Recitation Homework 4 Written and Homework 4 Programming due Sunday
5 Mon: Nov 18 Trees and lists [Slides] [Reference (5.2-5)] [Reference (6.2-5)]
5 Wed: Nov 20 Quiz 2 + Stacks and Queues [Slides] [Reference (6.6-8)]
5 Fri: Nov 22 Recitation
6 Mon: Nov 25 Graphs [Slides] [Reference (9.2-6)]
6 Wed: Nov 27 No class
6 Fri: Nov 29 No recitation Homework 5+6 due Sunday
7 Mon: Dec 2 Optimization [Slides] [Notes on search]
7 Wed: Dec 4 Optimization
7 Fri: Dec 6 Quiz 3 Homework 7 loss_optimization.py due Sunday

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