Book Image

The Kaggle Workbook

By : Konrad Banachewicz, Luca Massaron
5 (1)
Book Image

The Kaggle Workbook

5 (1)
By: Konrad Banachewicz, Luca Massaron

Overview of this book

More than 80,000 Kaggle novices currently participate in Kaggle competitions. To help them navigate the often-overwhelming world of Kaggle, two Grandmasters put their heads together to write The Kaggle Book, which made plenty of waves in the community. Now, they’ve come back with an even more practical approach based on hands-on exercises that can help you start thinking like an experienced data scientist. In this book, you’ll get up close and personal with four extensive case studies based on past Kaggle competitions. You’ll learn how bright minds predicted which drivers would likely avoid filing insurance claims in Brazil and see how expert Kagglers used gradient-boosting methods to model Walmart unit sales time-series data. Get into computer vision by discovering different solutions for identifying the type of disease present on cassava leaves. And see how the Kaggle community created predictive algorithms to solve the natural language processing problem of subjective question-answering. You can use this workbook as a supplement alongside The Kaggle Book or on its own alongside resources available on the Kaggle website and other online communities. Whatever path you choose, this workbook will help make you a formidable Kaggle competitor.
Table of Contents (7 chapters)


When we started planning The Kaggle Book, we had more than 85,117 novices (as they have at least just registered) and 57,426 contributors (as they have at least filled their profile) present at the time on the Kaggle platform. We wondered how to help them break the ice with data science competitions on Kaggle. We then decided to provide them with the best available information about Kaggle and data science competitions and help them to start their journey in the best possible way, thanks to hints and suggestions by over 30 Kaggle Masters and Grandmasters.

Only when we had completed our work, we realized that there was little space left in the book for anything else and that, regrettably, we had to exclude some practical demonstrations and examples. However, practice sometimes is as important as theory (we know about it very well since we are applied data scientists!), and theory cannot be considered complete without any practice. Finally, The Kaggle Workbook is here to supplement The Kaggle Book by providing you with guided exercises to put some of the ideas found in The Kaggle Book into practice.

Strictly speaking, in this workbook, you will find:

  • The exploration of an emblematic selection of competitions (tabular, forecasting, computer vision, and natural language processing) where we demonstrate how a simple and effective solution can be derived for each of them.
  • Reference to concepts and ideas to be found in the original Kaggle Book.
  • Some challenges for the readers, as we pose some questions (and exercises) help hone your skills on the same proposed competitions or in analogous ones.

First, by reading The Kaggle Book and then practicing on The Kaggle Workbook, you’ll have all the skills, both theory-based and hands-on, necessary to compete on Kaggle for glory, fun, or learning, and gathering interesting, applied projects to present in a job interview, or for your own portfolio!

Let’s not wait; let’s start practicing now!