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

The Meta Kaggle dataset

The Meta Kaggle dataset (https://www.kaggle.com/kaggle/meta-kaggle) is a collection of rich data about Kaggle’s community and activity, published by Kaggle itself as a public dataset. It contains CSV tables filled with public activity from Competitions, Datasets, Notebooks, and Discussions. All you have to do is to start a Kaggle Notebook (as you saw in Chapters 2 and 3), add to it the Meta Kaggle dataset, and start analyzing the data. The CSV tables are updated daily, so you’ll have to refresh your analysis often, but that’s worth it given the insights you can extract.

We will sometimes refer to the Meta Kaggle dataset in this book, both as inspiration for many interesting examples of the dynamics in a competition and as a way to pick up useful examples for your learning and competition strategies. Here, we are going to use it in order to figure out what evaluation metrics have been used most frequently for competitions in the last...