Skip to content
HomeVideos
AllLongsCategoriesPlaylists
BooksBlogsPodcasts
HistoryListsWatch laterLiked videosFollowing

The videos, books, blogs and podcasts Hacker News keeps recommending, all in one place.

VideosBooksBlogsPodcastsAboutPrivacySettings

Data from Hacker News, HackerTube, HackerBooks, HackerBlogs and Open Library. Credits · Not affiliated with Y Combinator.

HomeVideosBooksBlogsPodcasts
Ctrl K

    Lec 1 | MIT 18.06 Linear Algebra, Spring 2005

    MIT OpenCourseWare

    11 HN recommenders · recommended in 13 months, 2011–2020

    YouTube

    39:49 · 4.9M views · May 7, 2009

    The first lecture of Gilbert Strang's MIT 18.06 Linear Algebra course, covering the geometry of linear equations. It opens a full 35-lecture university course.

    It is HN's default recommendation for learning linear algebra, praised for Strang's teaching and for building real understanding useful in machine learning.

    Ideas, Learning & LanguageUniversity lectures & coursesPure mathematics
    1. 44:09
      Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010MIT OpenCourseWare2.8M views • 13 years ago
    2. 1:12:56
      Lecture 1A | MIT 6.001 Structure and Interpretation, 1986MIT OpenCourseWare995K views • 17 years ago
    3. 9:52
      Vectors | Chapter 1, Essence of linear algebra3Blue1Brown13M views • 10 years ago
    4. 53:30
      Lec 1 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008MIT OpenCourseWare6.6M views • 17 years ago
    5. 1:12:56
      Lecture 1A: Overview and Introduction to LispMIT OpenCourseWare421K views • 7 years ago
    6. 5:09
      Essence of linear algebra preview3Blue1Brown2.8M views • 10 years ago
    7. 1:20:33
      Lecture 1 | Convex Optimization I (Stanford)Stanford754K views • 18 years ago
    8. 51:47
      Lecture 19: Dynamic Programming I: Fibonacci, Shortest PathsMIT OpenCourseWare2.9M views • 13 years ago
    9. 1:08:40
      Lecture 1 | Machine Learning (Stanford)Stanford2.7M views • 18 years ago
    10. 1:02:06
      Real Analysis, Lecture 1: Constructing the Rational NumbersHarveyMuddCollegeEDU613K views • 16 years ago
    11. 32:06
      Preface | MIT Calculus Revisited: Single Variable CalculusMIT OpenCourseWare359K views • 15 years ago
    12. 1:20:11
      17. Succinct Structures IMIT OpenCourseWare17K views • 12 years ago
    13. 1:00:34
      1. Introduction, Finite Automata, Regular ExpressionsMIT OpenCourseWare628K views • 5 years ago
    14. 1:02:34
      MIT Godel Escher Bach Lecture 1jasonofthel33t557K views • 13 years ago
    15. 46:46
      Category Theory 1.1: Motivation and PhilosophyBartosz Milewski394K views • 10 years ago
    16. 17:16
      Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra3Blue1Brown6.4M views • 10 years ago
    17. 58:22
      Lecture 1B | MIT 6.001 Structure and Interpretation, 1986MIT OpenCourseWare116K views • 17 years ago
    18. 48:55
      Pythagoras' theorem (a) | Math History | NJ WildbergerInsights into Mathematics518K views • 15 years ago
    19. 1:02:15
      Lambda Calculus - Fundamentals of Lambda Calculus & Functional Programming in JavaScriptFullstack Academy228K views • 9 years ago
    20. 49:47
      Lecture 1 | Programming Methodology (Stanford)Stanford2.6M views • 18 years ago

    15 comments from Hacker News

    1. @olooneyMay 2019· in “Self Studying the MIT Applied Math Curriculum”

      I did Strang's linear algebra course[0] (link goes to Youtube playlist of lectures) several years after graduating and recommend it highly. I was looking for refresher but I gained a deeper understanding of several important concepts; in particular it's fair to say I barely understood, or perhaps even misunderstood, SVD until Strang. If you're not sure if you need something like that, I suggest doing something like testing yourself on this video[1] or the MIT problem sets[2] it's easy to tell yourself that you "know" linear algebra when it would be closer to the truth to say that you used to know linear algebra, but can't answer even basic questions today. After Strang, Golub's book on Matrix Computations is also really incredible.[3] [0]: this video [1]: [LINK] [2]: [LINK] [3]: [LINK]

      Strongly recommendsView on HN
    2. @raz32dustFeb 2015· in “How to Machine Learn”

      Useful list. I would recommend adding one more resource for linear algebra/machine learning: I absolutely enjoyed learning Linear Algebra from these beautiful lectures by Prof. Gilbert Strang (MIT): this video Seriously, I gained a new found appreciation for Linear algebra after going through these lectures. You should go over some of these lectures even if you already know linear algebra - it might give you insights you never had before (it did, for me). Absolute must-watch if you are into machine learning or related areas.

      Strongly recommendsView on HN
    3. @palebluedotSep 2011· in “Surprises from numerical linear algebra (2010)”

      I highly recommend the MIT 18.06 open course on linear algebra - the lectures are first rate. I've been going through this as a refresher, in prep for the Stanford machine learning class. Link to the course: [LINK] Link to the YouTube videos of the lectures: this video

      Strongly recommendsView on HN
    4. @SantalBlushMay 2019· in “Gilbert Strang's New Course on Linear Algebra+ for ML Now Online”

      Love Gilbert Strang's original linear algebra lectures on YouTube [1]. They were a huge help while I took the course. In my opinion, he takes great care to motivate each topic and express his train of thought when working through problems. [1] this video

      Strongly recommendsView on HN
    5. @yesenadamFeb 2019· in “Ask HN: Linear algebra textbooks”

      Gilbert Strang's Linear Algebra course from MIT, available on youtube (3 million views!), and his textbook of the same name are awesome. What a great teacher. this video

      Strongly recommendsView on HN