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

Finding New Professional Opportunities

After introducing how to better highlight your work and achievements in competitions in the previous chapter, we will now conclude our overview of how Kaggle can positively affect your career. This last chapter discusses the best ways to leverage all your efforts to find new professional opportunities. We expect you now have all the previously described instruments (your Kaggle Discussions, Notebooks, and Datasets, and a GitHub account presenting quite a few projects derived from Kaggle), so this chapter will move to softer aspects: how to network and how to present your Kaggle experience to recruiters and companies.

It is common knowledge that networking opens up many possibilities, from being contacted about new job opportunities that do not appear on public boards to having someone to rely on for data science problems you are not an expert in. Networking on Kaggle is principally related to team collaboration during competitions and connections...