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Hi, everyone.
In this video we'll learn how to use Kaggle for
participation in data science competitions.
Let's open kaggle.com.
On the Competitions page, we can see a list of currently running competitions.
Every competition has a page which consists of title, short description,
price budget, number of participating teams, and time before the end.
Information involves all previously running competitions,
we can find if we click to All.
Let's select some challenge and see how it organized.
Here, we see several tabs which we'll explore, and let's start with Overview.
In the Description section we see an introduction provided by organizers.
In the Description, there is a short story about company and tasks,
sometimes with illustration.
At the Evaluation page, we see the description of the target metric.
In this challenge, target metric is the Mean Absolute Error between
the logarithmic transform predictions and ground truth values.
This page also contains example of sample submission file, which is typical for
such kind of competitions.
Now let's move to the Prize page.
In the Prize, page we can find information about prizes.
Take notice that in the title we have information about the whole money budget,
and this page, we see how it will be split among winners.
I want to highlight that in order to get money,
you need not only be in top three teams, but also beat a Zillow benchmark model.
Now let's see, Timeline page, which contains all the information about dates.
For example, when competition starts, ends,
when will the Team Merger deadline and then what month.
All the details about competition, we can find in the Rules.
So we need to check really the rules.
Here we can find that team limit is three individual,
that we have maximum of five submissions per day, that you,
for example, should be at least 18 years old to participate.
And that, find it,
that external data are not allowed.
I strongly suggest you to read the rules carefully before joining the competition.
And after reading, you should accept it, but I already accepted it.
Now, let's check this, Data.
Here we have data provided by the organizers, several files which we can
download, and sample submission among them, and the description of the data.
Here we have description of files, description of data fields, and
more importantly a description of train and test split.
This is quite useful information in order to set up right validation scheme.
If you have any question about data or other questions to ask, or insights to
share, you can go to the forum, which we can find under Discussion tab.
Usually it contain a lot of topics or threads, like Welcome, questions about
validations, questions about train and test data, and so on and so on.
Every topic have title, number of comments, and number of reports.
Let's see some of them.
Here we have main message, a lot of comments,
in this particular we have only one comments.
Each we can up vote or down vote and reply to by click the reply button.
That was a brief overview on forum and now we switch to the Kernels.
Usually, I run my code locally, but sometimes it would be handy
to check an idea quickly or share code with other participants or teammates.
This is what Kernels are for.
You can think of Kernel as a small virtual machine in which you write your code,
execute it, and share it.
Let's take a look at some Kernel, for example for this one.
This show explanatory data analysis on the Zillow competition.
It took quite long, contain a lot of pictures, and I believe it very useful.
Here we can see comments for this, different versions.
And in order, if you want to make a copy and edit it,
we need to Fork this Notebook.
It doesn't matter how your predictions were produced, locally or
by Kernel, you should submit them through a specialized form.
So go back to the competition.
Go to submissions.
I already submit sample submission, you can do the same.
Click submit predictions, and drag and drop file here.
Let's look at my submission.
After submission, you will see it on the leaderboard.
This is my sample submission.
Leaderboard contains information about all the teams.
So here we have team name or just name in case of single competition team.
Score which we produced, number of submissions,
time since the last submissions, and position data over seven last days.
For example, this means that this guy drops 19 positions during the last week.
That was a brief overview of Kaggle interface.
Further, I will tell some extra information about the platform.
So let's move to Overview page at the bottom.
And here, we see information about points and tiers.
As mentioned here, the competition will be counting towards ranking points an tiers.
If you participate, it will be beneficial for your rating.
Sometimes, especially in educational competitions, it's not like that.
Information about Kaggle Progression System we can find if we click this link,
where we can read information about tiers like novice, contributor, master,
grandmaster.
About medals and ranking points.
This ranking points, I use for global User Ranking.
Let's check it.
So, we have user ranking page, and
we see all the users ranked, and with links to their profile.
Let's check some profile, for example mine.
And here we have photo, name, some information,
geo information, information about past competitions, medals, and so on.
In addition, I want to say a few words about ability to host competition.
Kaggle has this ability.
Click Host competition, and there is special Kaggle in class.
At in class, everyone can host their own competition for free and
invite people to participate.
This option is quite often used in various educational competitions.
So this was a brief overview of Kaggle platform.
Thank for your attention.
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