Winning a Kaggle Competition in Python

Name: Winning a Kaggle Competition in Python
Brand: Careervira
Price: 150 USD
Availability: InStock
Rating: 1 (1 reviews)

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DataCamp

Course Report

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Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

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

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Data Manipulation with pandas

Extreme Gradient Boosting with XGBoost

Supervised Learning with scikit-learn

What You Will Learn

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

Learn how to approach and win competitions on Kaggle

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 Content

Expand all sections

Module 1: Kaggle competitions process

Module 2: Dive into the Competition

Module 3: Feature Engineering

Module 4: Modeling

Course Instructors

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...