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  • GILBERT STRANG: Hi, I'm Gilbert Strang, and professor

  • of mathematics at MIT.

  • And I get a chance to say a few words

  • about 18.06, Linear Algebra.

  • It's one of the basic math courses.

  • Can I say a little about linear algebra itself?

  • Classes in linear algebra earlier years tended

  • to be pretty much for pure math majors, and a lot of proofs,

  • and usefulness of the subject kind of wasn't so clear.

  • Whereas, it's an incredibly useful subject.

  • Data is coming in all the time.

  • We're in the century of data, and data

  • tends to come in a matrix, in a rectangular array of numbers.

  • And how to understand that data is a giant, giant problem.

  • And people use matrices in solving differential equations

  • in economics, everywhere.

  • So the subject had to change to bring out

  • this important aspect, that it's terrifically useful.

  • Often networks are a great model,

  • where you have like-- like the internet.

  • Every website would be like a node in the network.

  • And if one website is linked to another one,

  • there would maybe be an edge in that network.

  • So that's a network with a billion nodes.

  • And a matrix describes all those links.

  • Like when Google produces a PageRank, you enter-- well,

  • you could enter linear algebra, and see what happens.

  • I don't know.

  • I hope something good.

  • Well, anyway, thousands and millions of stuff

  • would come up ranked in order, and that order

  • comes from operating-- Google's very fast at it,

  • very good at it-- operating on that giant matrix that

  • describes the internet.

  • OK, so a word about the course itself-- the MIT course.

  • First of all, there will be students coming

  • from all the departments.

  • That includes management.

  • Business data comes in matrix form

  • just the way engineering data comes.

  • So there is hardly a prerequisite for the course.

  • There's no big reason why calculus has to come first.

  • Probably most MIT students will know before the course starts--

  • they will have multiplied a matrix by a vector,

  • or multiplied two matrices.

  • So they've at least seen matrices before.

  • But anybody could catch up on that quickly.

  • And then, the course just takes off.

  • Actually, we go back to ask, how do you understand multiplying

  • a matrix by a vector?

  • A key-- yeah, you guys will probably know how to do it,

  • but let me say it another way-- A matrix times a vector

  • produces a combination of the columns in that matrix,

  • those column vectors in the matrix.

  • So that's like the key step in linear algebra.

  • What you can do with vectors is take linear combinations.

  • Well, at MIT, the course is organized with three lectures

  • a week.

  • And I use the chalkboard.

  • I hope you feel, in watching them, that that's OK.

  • The nice thing about a chalkboard

  • is you get to see-- what's written doesn't disappear.

  • So your eye can continually check back

  • and see how does it connect with what's happening at the moment.

  • And then, there is one hour a week of recitation.

  • Because that's a smaller class, it just

  • means there's a teaching assistant

  • there, who can help with problems, suggest new problems.

  • It can be a problem-based hour, where my lectures are

  • more explanation hours.

  • So about the textbook.

  • The homeworks come from the book mostly.

  • Sometimes we add MATLAB problems, sort

  • of specially constructed ones.

  • But the central ideas of the subject

  • are described in each section of the book,

  • and then, naturally, exercises to practice with those ideas.

  • And then, the neat thing about 18.06 Scholar

  • is you get short lectures, short videos, from six different TAs,

  • did about six problem-solving videos each.

  • And they are neat.

  • The TAs are good.

  • And that's something that can happen in the recitation

  • with a smaller group.

  • There's chance for a discussion, whereas in the lecture-- well,

  • I still ask questions in the lecture,

  • as you'll probably see.

  • But it's a little harder for students

  • to shout out an answer, so they can shout all

  • they want in their recitations.

  • With each lecture, we produce a written summary

  • of what it's about.

  • So after you watch the lecture, you could look at that summary

  • and it reinforces, remembering the key points of the lecture.

  • And then we also added in some problems, four or five

  • problems from the book that you can just look at and see, OK,

  • do I know what the question is here?

  • Do I know how to do it?

  • I think, as a result, you're learning linear algebra.

  • A thought or two about linear algebra

  • worldwide, because it really is worldwide.

  • The feedback comes from all over the world.

  • It's really nice to get.

  • Also, I enjoy going.

  • So if somebody invites me to Egypt or Australia or China,

  • I tend to go if I can.

  • Because that's a lovely part about mathematics.

  • It's really universal.

  • It's a language almost of its own

  • that everybody can learn to speak.

  • And I hope these lectures help.

GILBERT STRANG: Hi, I'm Gilbert Strang, and professor

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課程介紹|MIT 18.06SC 線性代數 (Course Introduction | MIT 18.06SC Linear Algebra)

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    林宜悉 發佈於 2021 年 01 月 14 日
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