5 - 7 - Working on and Submitting Programming Exercises (4 min).srt

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在这段视频中 我想很快地介绍一下这门课程
(字幕整理：中国海洋大学 黄海广,haiguang2000@qq.com )

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In this video, I want to just quickly step you
through the logistics of how to work on

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做作业的流程 以及如何使用作业提交系统

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homeworks in this class and how to use the
submission system which will let you verify

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这个提交系统可以即时检验你的机器学习程序答案是否正确

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right away that you got the right answer for
your machine learning program exercise.

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这是我的 Octave 编程窗口 让我们先进入到我的桌面

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Here's my Octave window and
let's first go to my desktop.

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我在我的桌面上保存了我的第一个练习和一些文件

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I saved the files for my first exercise,
some of the files on my desktop:

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在 'ml-class-ex1' 目录中

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in this directory, 'ml-class-ex1'.

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我们提供了大量的文件 其中有一些需要由你自己来编辑

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And we provide a number files
and ask you to edit some of them.

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因此第一个文件应该符合编程练习中 pdf 文件的要求

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So the first file should meet the details in
the pdf file for this programming exercise.

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其中一个我们要求你编写的文件是 warmUpExercise.m 这个文件

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But one of the files we ask you to edit is
this file called warmUpExercise.m, where the

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这个文件只是为了确保你熟悉提交系统

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exercise is really just to make sure that
you're familiar with the submission system.

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所有你需要做的就是提交一个5×5的矩阵

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And all you need to do is
return the 5x5 identity matrix.

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因此这个练习的答案 我给你们写过 就是 A = eye(5)

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So the solution to this exercise I just
showed you is to write A = eye(5).

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这将修改该函数以产生5×5的单位矩阵

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So that modifies this function to
generate the 5x5 identity matrix.

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现在warmUpExercise() 这个方程就实现了返回5x5的单位矩阵

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And this function warmUpExercise()
now returns the 5x5 identity matrix.

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将它保存一下

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And I'm just going to save it.

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所以我已经完成了作业的第一部分 现在回到我的 Octave 窗口

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So I've done the first part of this homework.
Going back to my Octave window,

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现在来到我的目录 C:\Users\ang\Desktop\ml-class-ex1

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let's now go to my directory,
'C:\Users\ang\Desktop\ml-class-ex1'.

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如果我想确保我已经实现了程序 像这样输入'warmUpExercise()'

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And if I want to make sure that I've implemented
this, type 'warmUpExercise()' like so.

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好了它返回了我们用刚才写的代码创建的一个5x5的单位矩阵

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And yup, it returns the 5x5 identity matrix
that we just wrote the code to create.

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我现在可以按如下步骤提交代码 我要在这里目录下键入 submit()

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And I can now submit the code as follows.
I'm going to type 'submit()' in this

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我要提交第一部分 所以我选择输入'1'

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directory and I'm ready to submit part 1
so I'm going to enter choice '1'.

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这时它问我我的电子邮件地址 我们打开课程网站

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So it asks me for my email address.
I'm going go to the course website.

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这是一个内部测试网站 所以你的版本可能看起来有点不同

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This is an internal testing site, so your version
of the website may look a little bit different.

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这是我的电子邮件地址 和我的提交密码 我需要在这里输入

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But that's my email address and this is my submission
password, and I'm just going to type them in here.

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所以我的邮箱是 ang@cs.stanford.edu 我的提交密码就是 9yC75USsGf

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So I have ang@cs.stanford.edu and
my submission password is 9yC75USsGf.

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按下回车键 它连接到服务器 并将其提交

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I'm going to hit enter; it connects to the server
and submits it, and right away

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然后它就会立刻告诉你 恭喜您 已成功完成作业1第1部分

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it tells you "Congratulations! You have
successfully completed Homework 1 Part 1".

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这就确认了你已经做对了第一部分练习

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And this gives you a verification
that you got this part right.

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如果你提交的答案不正确 那么它会给你一条消息 说明

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And if you don't submit the right answer,
then it will give you a message indicating

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你没有完全答对

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that you haven't quite gotten it right yet.

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您还可以继续使用此提交密码 也可以生成新密码 都没有关系

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And you can use this submission password and
you can generate new passwords; it doesn't matter.

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但你也可以使用你的网站登录密码 但因为这个密码

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But you can also use your regular website
login password, but because this password

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会在显示器上直接显示 所以我们给你额外的提交密码

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here is typed in clear text on your monitor,
we gave you this extra submission password

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因为你可能不希望输入你登录网站的密码

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in case you don't want to type in your
website's normal password onto a window

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你的密码是否会显示出来 取决于你使用的操作系统

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that, depending on your operating system,
may or may not appear as text when you type

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你的密码是否会显示出来 取决于你使用的操作系统

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it into the Octave submission script.

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这就是提交作业的方法

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So, that's how you submit the
homeworks after you've done it.

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祝你好运 当你完成家庭作业的时候 我希望你都能答对

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Good luck, and, when you get around to
homeworks, I hope you get all of them right.

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最后 在下一个也就是最后一个 Octave 的视频教程中 我将介绍

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And finally, in the next and final Octave
tutorial video, I want to tell you about

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向量化(vectoriazation) 这种方式可以使你的 Octave 代码更有效率地运行

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vectorization, which is a way to get your
Octave code to run much more efficiently.