THE VIDEO SHELF · convex optimization
Lecture 1 | Convex Optimization I (Stanford)
The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.
Why HN readers recommended it
HN recommends Boyd's lectures as a fantastic, often funny follow-up to linear algebra and as a step in machine learning study paths.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- Stanford
- Topic
- convex optimization
- Format
- lecture
- Level
- intermediate
- HN recommenders in dataset
- 2
- HN mentions in dataset
- 4
- Recommendation years in dataset
- 2011–2022
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
These lectures are fantastic after you've mastered the basics of linear algebra [VIDEO] (convex optimization, by a very experienced and often funny lecturer)
natly on Hacker News · 2022-05
In The big six matrix factorizationsThis is my favorite way to think about it as well. I think I learned it first in one of Steven Boyds astounding convex optimization lectures [VIDEO]
hwers on Hacker News · 2022-01
In Matrix Multiplication
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.