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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Designing Good Validation

In a Kaggle competition, in the heat of modeling and submitting results, it may seem enough to take at face value the results you get back from the leaderboard. In the end, you may think that what counts in a competition is your ranking. This is a common error that is made repeatedly in competitions. In actual fact, you won’t know what the actual leaderboard (the private one) looks like until after the competition has closed, and trusting the public part of it is not advisable because it is quite often misleading.

In this chapter, we will introduce you to the importance of validation in data competitions. You will learn about:

  • What overfitting is and how a public leaderboard can be misleading
  • The dreadful shake-ups
  • The different kinds of validation strategies
  • Adversarial validation
  • How to spot and leverage leakages
  • What your strategies should be when choosing your final submissions

Monitoring your...