Book Image

The Kaggle Book

By : Konrad Banachewicz, Luca Massaron
5 (2)
Book Image

The Kaggle Book

5 (2)
By: Konrad Banachewicz, Luca Massaron

Overview of this book

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you’ll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won’t easily find elsewhere, and the knowledge they’ve accumulated along the way. As well as Kaggle-specific tips, you’ll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You’ll design better validation schemes and work more comfortably with different evaluation metrics. Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you. Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!
Table of Contents (20 chapters)
Part I: Introduction to Competitions
Part II: Sharpening Your Skills for Competitions
Part III: Leveraging Competitions for Your Career
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Competition Tasks and Metrics

In a competition, you start by examining the target metric. Understanding how your model’s errors are evaluated is key for scoring highly in every competition. When your predictions are submitted to the Kaggle platform, they are compared to a ground truth based on the target metric.

For instance, in the Titanic competition (, all your submissions are evaluated based on accuracy, the percentage of surviving passengers you correctly predict. The organizers decided upon this metric because the aim of the competition is to find a model that estimates the probability of survival of a passenger under similar circumstances. In another knowledge competition, House Prices - Advanced Regression Techniques (, your work will be evaluated based on an average difference between your prediction and the ground truth. This involves computing the logarithm...