Hello everyone, 
Thanks for participating in our LightAutoML course!

In this competition the task is to predict the cars prices based on information about them.

There are several baselines for this competition:

<ul>
	<li>All zeros baseline</li>
	<li>Mean train price baseline</li>
	<li>Median train price baseline</li>
	<li><a href="https://www.kaggle.com/alexryzhkov/lightautoml-starter-for-hw1">LightAutoML simple baseline</a></li>
	<li><a href="https://www.kaggle.com/alexryzhkov/lightautoml-hw1-better-baseline">LightAutoML real baseline</a></li>
	<li><a href="https://www.kaggle.com/alexryzhkov/lightautoml-hw-1-with-custom-fe">LightAutoML stronger baseline</a></li>
</ul>

Let&#39;s beat all of them!

P.S. If you like LightAutoML, do not forget to support us with the star on <a href="https://github.com/sberbank-ai-lab/LightAutoML">Github</a>.

Predict car prices using LightAutoML framework

Public

Evaluation

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first_name

First name

last_name

Last name

country

Country

city

City

email

Email

slack_name

Your ODS Slack nickname

study_place

Study place

study_specialty

Study specialty

work_place

Work place

work_position

Work position

expectations

Expectations

interests

Interests

preferred_language

Preferred language

about

About

Registration application for Course Season 2021

LightAutoML course homework 1

Predictions

The metric for this competition is MAE - mean absolute error. 
More info <a href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html">here</a>

Your submission should look like <code>sample_submission.csv</code> file - contains 10697 rows with predictions for <code>row_ID</code> from 35000 to 45696 inclusively.