Hi! I'm Ian Witten from the beautiful University of Waikato here in New Zealand, and I want
to tell you about our new online course: Advanced Data Mining with Weka.
If you liked the other courses--Data Mining with Weka and More Data Mining with Weka--you'll
love this new course.
It's the same format, the same software, the same learning by doing, and the aim is the
same, too: to show you how to use powerful techniques of data mining on your own data.
One difference is that the lessons in this course are given by different people.
In fact, you'll get to meet pretty well the whole Weka team in this course.
This new course is advanced.
We're going to be looking at new kinds of data.
We're going to be looking at time series, for example, where the data evolves over time
and your job is to predict the future.
Or situations where the characteristic of the source changes slowly over time,
like it does in real life, and your job is to track those changes.
We'll look at different ways of working with big data.
We're going to introduce you to Weka's big sister, Moa, which is a stream-oriented data
mining system that never stores the data in main memory, so it can operate on effectively
infinite streams of data and has to use special algorithms to deal with these streams,
which we'll explain to you.
We'll also show you how to deploy Weka on a cluster computing environment using the Apache
Spark framework, and also the popular Hadoop framework.
We're going to show you how you can reach out to other data mining systems from Weka,
for example, the popular R data mining system.
You can get at all the algorithms in R, all the mining algorithms and all the
very powerful information display capabilities right there within your Weka interface.
We'll look at scripting Weka in Python, and you can write little Python scripts right
there in the Weka interface.
We'll show you how to set up the Python Weka wrapper, where you can access the Weka API
right from within your very own Python program.
By popular demand, we've included some applications.
We'll talk about the application of Weka to soil sample analysis, where machine learning
can effectively replace time consuming wet chemistry.
We'll look at signals from your brain, functional MRI signals, which treats the brain as a set
of voxels that extends over time, a kind of four-dimensional dataset of what's happening
in your brain and how to analyze this kind of data.
We'll look at a bioinformatics application: signal peptide prediction.
We'll look at some image processing stuff, some filters for getting features off images;
and we'll look at a Twitter application where you use Weka to do text mining on a Twitter
feed.
This course is aimed at teaching you the principles and practice of data mining.
We don't look at the technical details of particular algorithms.
In fact, you don't need any special mathematical background to do this course.
Indeed, you don't need any programming background.
We'll see some little Python programs, but you can pick that up along the way.
We'll show you how, don't worry.
Other things for this course ... You're going to need a computer, of course.
You're going to need an internet connection.
You're going to need a Google account, because again we're using the Google infrastructure
to deliver the course.
You will need a few hours a week each week.
You'll need a lot of motivation.
This is difficult stuff.
You're going to learn a lot.
The course lasts five weeks.
There are six lessons each week, and each lesson comprises a short video like this one,
followed by an activity where you get to practice what you've learned on a dataset that we provide.
And there are a couple of tests:
if you do well enough in those, you'll receive a statement of completion from the University
of Waikato, signed by me.
What else? Textbook? There is no textbook.
This stuff isn't in the books.
And I've recorded a new piece of music for you, some improvisations on a jazz theme by Dizzy Gillespie.
And the price of admission is zero.
This course is absolutely free.
So that's it.
Advanced Data Mining with Weka, coming soon to a computer near you.
Hope to see you there.
Bye for now!