Name: ジョシュ・ゴードンとのコーヒーで機械学習 - グーグラーとのコーヒー (Machine Learning over Coffee with Josh Gordon - Coffee with a Googler)
Uploaded: 2021-01-14T06:26:28.000Z
Duration: 6 min 37 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

LAURENCE MORONEY: Today I'm in the Big Apple

we will dig into how it works, why it's important,

Welcome to Coffee with a Googler in New York City.

don't really understand what machine learning is

JOSHUA GORDON: So the short way of saying

that is regular programming is you write a lot of manual rules

In machine learning, you let the algorithm

It might be visual, or it might be other patterns

And so the input to machine-- so the beauty of machine learning,

and the real secret sauce, is that an algorithm that

learns patterns from data can solve thousands

And the reason is if I write a Python program to recognize

digits, my program is hard coded to work with digits.

JOSHUA GORDON: But if I write an algorithm to learn patterns

from data, I can use that for speech recognition, image

Basically, anything that you can start with examples,

just tell apart A and B, my same algorithm that I wrote just

And that's a really special and actually fairly profound thing.

Now, one of the things in your classes that you're

talking about that you're starting with language.

who want to be these data scientists of the future?

So first of all, there are zero prerequisites.

JOSHUA GORDON: Basic programming ability in Java or Python.

And by basic, I mean you can run scripts and you can tweak them.

And that means like basic algebra, basic geometry.

When I say basic geometry, to be totally honest,

if you asked me, like, what sine and cosine,

So just basic familiarity, and that's it.

And we're going to teach the class in three ways.

We're going to teach it totally from the ground up.

So one problem I had with some of the academic classes I took

is that they'll talk about a fancy algorithm,

And so at the end of the class, I don't know how to build that.

We're building it step by step, and we're

explaining only the math that's really necessary as we go.

And instead of equations, we're going use visual examples.

be like if you talk about gradient descent,

So if I just say that, like as a developer, I'm like, all right,

like x cubed plus y squared plus whatever equals 7.

LAURENCE MORONEY: That's going to be the bottom of that curve,

Anyway, you can find the bottom of that curve

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ジョシュ・ゴードンとのコーヒーで機械学習 - グーグラーとのコーヒー (Machine Learning over Coffee with Josh Gordon - Coffee with a Googler)

absolutely

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