Winning a Kaggle Competition in Python

Course Description

Kaggle is the most famous platform for Data Science competitions. Taking part in such competitions allows you to work with real-world datasets, explore various machine learning problems, compete with other participants and, finally, get invaluable hands-on experience. In this course, you will learn how to approach and structure any Data Science competition. 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. All these techniques will be practiced on Kaggle competitions datasets.

In the following tracks

Machine Learning Scientist

Datasets

Demand forecasting (train)Demand forecasting (test)House prices (train)House prices (test)Taxi rides (train)Taxi rides (test)

Collaborators

Hadrien LacroixHillary Green-Lerman

Prerequisites

Manipulating DataFrames with pandasSupervised Learning with scikit-learnExtreme Gradient Boosting with XGBoost

Yauhen Babakhin

Kaggle Grandmaster

Yauhen holds a Master’s 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 competitions Grandmaster in Belarus having gold medals in both classic Machine Learning and Deep Learning competitions.

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