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Winning a Kaggle Competition in Python

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$12

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Kaggle is the most popular platform for Data Science contests. These competitions allow you to work directly with real data and solve machine learning problems. This course will help you structure and approach any Data Science competition. This course will teach you how to select the best local validation scheme and how to avoid overfitting. Advanced feature engineering and model assembly techniques will be covered. These techniques can also be applied to Kaggle competition datasets.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

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Supervised Learning with scikit-learn

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Extreme Gradient Boosting with XGBoost

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Data Manipulation with pandas

What You Will Learn

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Learn how to approach and win competitions on Kaggle

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In this course, you will learn how to approach and structure any Data Science competition

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You will be able to select the correct local validation scheme and to avoid overfitting. Moreover, you will master advanced feature engineering together with model ensembling approaches

Course Instructors

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Yauhen Babakhin

Kaggle Grandmaster

Yauhen holds a Master Degree in Applied Data Analysis and has over 5 years of working experience in Data Science. He worked in Banking, Gaming and eCommerce domains. Yauhen is also the first Kaggle c...

Course Reviews

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Course Cover

$12

$6

49% OFF

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