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)
Preface
1
Part I: Introduction to Competitions
6
Part II: Sharpening Your Skills for Competitions
15
Part III: Leveraging Competitions for Your Career
18
Other Books You May Enjoy
19
Index

Building connections with other competition data scientists

Connections are essential for finding a job, as they help you get into contact with people who may know about an opportunity before it becomes public and the search for potential candidates begins. In recent years, Kaggle has increasingly become a place where you can connect with other data scientists, collaborate, and make friends. In the past, competitions did not give rise to many exchanges on forums, and teams were heavily penalized in the global rankings because competition points were split equally among the team members. Improved rankings (see https://www.kaggle.com/general/14196) helped many Kagglers see teaming up in a more favorable light.

Teaming up in a Kaggle competition works fine if you already know the other team members and you already have an established approach to assigning tasks and collaborating remotely. In these situations, each team member already knows how to collaborate by:

  • Taking...