Hello, everyone. In this video,
we will talk a little bit about the main assignment of this course,
the competition, which plays the role of the final project.
Now, let's briefly discuss the data.
For more details, see the competition web page on Kaggle.
The data in this competition is quite challenging.
You can work with a time series data set consisting of daily sales data,
kindly provided by one of the largest Russian software company.
It's called 1C.
The training data consists of records with information that
a particular item had been sold in a particular shop,
in a particular day, in the training period.
The task is to forecast the sales for every item in every shop in the testing period.
There are about 6 million such records in the training set,
collected over 30 shops selling 20,000 unique items.
But don't be afraid of these numbers.
This is the moderate-sized competition data set nowadays.
The training period is about one and a half year,
and the testing period is the month that falls on training period.
Note that you provide these daily sales in training period.
Well, you need to predict aggregated sales for testing period.
That is, you need to predict monthly sales for every possible shop item pair.
In fact, correct aggregation of
overall daily sales and generation of appropriate features is a part of this challenge.
As in the majority of competitions,
that this data is split into public and private parts.
You can submit your test predictions up to five times every day on
Kaggle platform and up to five times every
week to Coursera's programming assignment grader.
Kaggle will evaluate the quality of your predictions on the public part of test set,
while Coursera's grader will report quality,
both in public and private parts.
That is, you can rarely peek at your private score.
Remember, the earlier you start working on the competition,
the more private score feedback you can get.
We encourage you to get familiar with the data
right away and not to wait until the very end.
Start simple and then improve your solution every week.
Remember, your final grades will depend on how would you have performed on
the private part of the leaderboard and on the quality of your solution report,
which will be graded by your peers.
You can read more about this in the reading material in the end of this week.
And, finally, the goal of the competition is to learn as much as possible,
so we strongly encourage you to participate in teams.
It is always fun and engaging.
In teams, you can discuss ideas and get feedback.
You can share a code and learn new tricks,
and you can get help if you're stuck.
If you don't have any teammates yet,
you can find them and meet them on forums.
Please never, never share your code on forums,
neither on Coursera forums,
nor on Kaggle's forums.
Sharing codes outside of the teams is strictly forbidden.
You are encouraged to share and discuss interesting ideas,
thoughts, even small quote snippets held by the learners,
but do not even share the complete code for your solution
because many people will blindly copy
paste your code without even trying to understand it.
It will reduce quality of skills acquired by fellow students,
it will ruin the fun of the fair competition.
On the other hand, every time you're stuck,
go in forums, and you will definitely find some inspiration there.
Good luck with the project and have fun.