Well, let's look at the confusion matrices!

吧，我们就来看看这混淆矩模型！

You can't make visual effects without vectors and matrices.

没有向量和矩就无法制作视觉效果。

They were asked to complete as many matrices as they could in three minutes.

他们被要求三分钟内完成尽可能多的矩。

There are a lot of things that make diagonal matrices much nicer to work with.

有很多东西可以使对角矩地工作。

Does it matter what order we put the two matrices in when we multiply them?

矩相乘时，它们的先后顺序影响结果吗？

Each of our 32 squares has 4 matrices, so that’s 32 thousand, 7 hundred and 68 bits.

我们的 32 方块中的每一都有 4 矩，所以是 32,000，700 和 68 位。

So far, we've been storing individual numbers or letters into our arrays or matrices.

到目前为止，我们一单数字或字母存储到我们的数组或矩中。

They are giant, inscrutable matrices of floating point numbers that we nudge in the direction of better performance until they inexplicably start working.

它们是无法参透的大型浮点数矩，我们朝着的性能试探着前进，到它们莫名其妙地运行起来。

And still with unit lengths. You often think of these as the rotation matrices.

还是单位长度 你通常认为这些是旋转矩。

That composition of three matrices gives us the transformation matrix.

三矩的组合给出了变换矩。

Most immediately, in the next video, I'll be talking about multiplying two matrices together.

最接的 下视频中 我讨论两矩相乘。

For instance, in the case of two by two matrices, rank two is the best that it can be.

例如 2×2矩的情况下 秩2是最的。

In the next video, I'll get into matrices in transforming space.

下视频中 我讨论变换空间中的矩。

They were given a sheet of paper with 20 matrices which each contained 12 numbers, two of which added up to ten (for example, 3.81 and 6.19).

每人持有一张印有20数的试卷，每数含12数字，两两相加为10（如3.81和6.19）。

E.G., here's a question Does it matter what order we put the two matrices in when we multiply?

例 这里有一问题 当我们把两矩相乘时 我们把它们按什么顺序排列有关系吗？

Next video, by popular request, will be a brief footnote about non square matrices.

下一视频 根据大家的要求 是一关于非方的简短脚注。

This video is No Exception, describing the concepts of inverse matrices, column space, rank and, uh no, space through that lens.

这视频是《无一例外》，描述了逆矩，列空间，秩，还有，不，通过这镜头的空间。

I showed what linear transformations looked like and how to represent them using matrices.

我展示了什么是线性变换以及如何用矩表示它们。

Multiplying two matrices is also similar.

两矩相乘也是类似的。

Always remember that multiplying two matrices like this has the geometric meaning of applying one transformation than another.

永远记住 像这样的两矩相乘具有应用一种变换而不是另一种变换的几何意义。