
English: 
Hi! I'm Ian Witten from the beautiful University
of Waikato in New Zealand,
and I'd like to tell you about our new online
course More Data Mining with Weka.
It's an advanced version of Data Mining with Weka,
and if you liked that,
you'll love the new course.
It's the same format, the same software,
the same learning by doing.
The aim is the same, as well, to enable you
to use advanced techniques of data mining
to process your own data 
and understand what you're doing.
You don't need to have actually completed
the old course in order to embark on the new one,
but we won't be covering things again,
so you will need to know something about data
mining and the Weka machine learning workbench.
The course has short, 5-10 minute video lessons.
Slides and captions are available, as well,
along with optional readings from
the data mining text book that the publisher

Chinese: 
大家好！我是Ian Witten， 来自美丽的新西兰怀卡托大学。
很高兴向大家介绍我们新开的网课More Data Mining with Weka。
 这门课是课程Data Mining with Weka的高阶部分。
如果你喜欢Data Mining with Weka，
你也会喜欢这门新课。
他们用同样的模式和软件，
同样的做中学。
学习目标也一样，是你能够使用数据挖掘的先进技术
处理手头的数据，并理解处理步骤。
你不需要学完之前的课程再学习新课程，
但是我们不会重复以前的知识。
因此，你需要了解数据挖掘和Weka机器学习工作台。
这门课由简短的，5-10分钟的视频组成。
课程还提供幻灯片、字幕
和选择性教材数据挖掘的课本。

English: 
has agreed to make available for free.
There is a mid-course assessment and an end-of-course
assessment, and if you do well in these,
you'll get a signed Statement of Completion from
the University of Waikato.
As before, Weka will be a laboratory for you
to learn the practice and the principles of
advanced data mining.
Each lesson is followed by a carefully designed
activity that reinforces what you learned
in the lesson.
You're going to do most of your learning actually
doing the activities.
You won't learn by listening to me talking
or watching me do things, you'll learn by
doing stuff yourself.
There won't be any programming in this course,
but a little bit of high school mathematics
might come in handy.
The topics were suggested by students who
completed the early course.
We're going to start by looking at how to
set up large scale experiments to compare
different learning and filtering techniques
on your own data and different versions of
the dataset.
Then you'll get to experience big data.

Chinese: 
出版商已经同意将其作为免费课程材料。
我们有期中和期末考试。如果你能顺利通过考试，
你就会获得怀卡托大学颁发的结业证书。
和以前一样，Weka作为你的实验室，帮助你练习和掌握
高阶数据挖掘的实践和原理。
每节课课后都有精心设计的练习，帮助你巩固
课堂内容。
实际上，大多情况下你需要在做中学。
你不可能通过听我讲课和看我做练习而达到学习的目的。
你是通过练习而学习的。
这门课不涉及任何编程知识，但需要有些高中数学的基础。
高中数学的基础。
课程内容是由之前学习基础课的同学建议的。
首先，我们来学习如何用大规模实验为你的数据
和不同版本的数集选择不同的的机器学习方法
和过滤技巧。
然后，我们尝试处理大规模数据。

Chinese: 
你将会处理成百上千万条数据
我会演示如何有效使用Weka
处理更多的数据。
之后，我们学习文本归类
文本挖掘是机器学习中一个很受欢迎的领域。
我们会学习相关的法则和聚类。
我们会学习属性选择和如何使用支出模型
来优化支出。
你还可以在Weka工具包中设置自己的神经网络。
当然，学习这门课，你需要一台电脑，
因为你需要在个人电脑上安装Weka。
你需要网络连接。
你还需要谷歌账号，
因为我们的网课用的是谷歌平台。
你需要强烈的动机和时间。
每周几小时，共5周时间。
这门课比上一门需要更多的时间，

English: 
You'll be working with datasets containing
many millions of instances,
and I'll show you how to use Weka to process
even larger,
effectively unlimited datasets, as well.
Then we'll look at document classification.
Text mining is a very popular application
of machine learning.
We'll look at association rules and clustering.
We'll look at attribute selection and how
to use cost models of your problem
to optimize the cost.
You'll even get to set up your own neural
network in the Weka toolkit.
Of course, you'll need a computer,
because you'll be installing Weka on your
own machine.
You need an internet connection,
and you'll need a Google account,
because we're using the Google infrastructure
again for the MOOC.
You'll need plenty of motivation, and you'll
need a bit of time, as well.
A few hours each week for the 5-week duration
of the course.
You should allow a little bit more for this
course than the previous one,

Chinese: 
因为这些练习更复杂，要求更高。
顺便说一句，我们编辑了新的音乐。
我们演奏朋友的乐曲。
你会喜欢听的。
实际上，我认为仅此音乐就值课程的学费，
学费为0.
另外，
这门课是完全免费的。
More Data Mining with Weka, More Data Mining with Weka
马上会来到你身边。
期待与您共同学习！

English: 
because the activities are more advanced and
a little bit more demanding.
By the way, we've got new music, as well.
We're playing something written by a friend of mine.
You'll love it.
In fact, the music alone I think is worth
the price of admission,
which is zero,
by the way.
This course is completely free.
More Data Mining with Weka,
coming soon to a computer near you!
Hope to see you there!
