math189r / math189r.github.io

HMC Mathematics of Big Data I Course Website

Harvey Mudd College 189r

Mathematics of Big Data I

Taught by Weiqing Gu

math189r.github.io's Issues

Notes: Lecture 7 - oct_24

Homework: 5 - nov_28

Section: Applications of EM: Hidden Markov Models

Section: Application: Identifying Rapidly Deteriorating Water Quality Locations With Gaussian Processes

Section: Application: Music Recommendation

Notes: Lecture 3 - sept_19

Section: Convex Optimization Overview I and II

Notes: Lecture 13 - dec_5

Notes: Lecture 2 - sept_12

Section: Probability Review

Notes: Lecture 10 - nov_14

Notes: Lecture 4 - sept_26

Notes: Lecture 9 - nov_7

Homework Page

Homework: 4 - nov_14

Section: Sparsity; SVM Training

Notes: Lecture 5 - oct_3

Notes: Lecture 1 - sept_5

Notes: Lecture 12 - nov_28

Midterm: Create Midterm

Notes: Lecture 8 - oct_31

Notes: Lecture 11 - nov_21

Homework: 3 - oct_31

Materials Page

Section: MapReduce and Distributed Computation and Learning

Section: Evaluating Models; Deployment

Homework: 1 - sept_19

Notes: Lecture 6 - oct_10

Linear Algebra review topics

I figured that someone should probably start some location with a collection of topics that we might want to cover during the review sessions (Thursdays from 6:30-9:15pm).

Personally, I would like it if we could review some of the topics that were covered in math 70 (or learn for those who haven't taken it yet). Concepts like

• Inner product spaces and related theorems
• The Gram-Schmidt procedure
• The Spectral and Real-Spectral theorems

Also, there were a few other concepts I wasn't familiar with-

• The Principal Axis Theorem
• Positive-definite matrices
• How linear algebra relates to polynomials of more than one variable

Did anyone else have any major topics that they wanted to cover?

Homework: 2 - oct_3