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The Kaggle Book

You're reading from   The Kaggle Book Data analysis and machine learning for competitive data science

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801817479
Length 534 pages
Edition 1st Edition
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Konrad Banachewicz Konrad Banachewicz
Author Profile Icon Konrad Banachewicz
Konrad Banachewicz
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Toc

Table of Contents (20) Chapters Close

Preface
1. Part I: Introduction to Competitions
2. Introducing Kaggle and Other Data Science Competitions FREE CHAPTER 3. Organizing Data with Datasets 4. Working and Learning with Kaggle Notebooks 5. Leveraging Discussion Forums 6. Part II: Sharpening Your Skills for Competitions
7. Competition Tasks and Metrics 8. Designing Good Validation 9. Modeling for Tabular Competitions 10. Hyperparameter Optimization 11. Ensembling with Blending and Stacking Solutions 12. Modeling for Computer Vision 13. Modeling for NLP 14. Simulation and Optimization Competitions 15. Part III: Leveraging Competitions for Your Career
16. Creating Your Portfolio of Projects and Ideas 17. Finding New Professional Opportunities 18. Other Books You May Enjoy
19. Index

Rock-paper-scissors

It is no coincidence that several problems in simulation competitions refer to playing games: at varying levels of complexity, games offer an environment with clearly defined rules, naturally lending itself to the agent-action-reward framework. Aside from Tic-Tac-Toe, connecting checkers is one of the simplest examples of a competitive game. Moving up the difficulty ladder (of games), let’s have a look at rock-paper-scissors and how a Kaggle contest centered around this game could be approached.

The idea of the Rock, Paper, Scissors competition (https://www.kaggle.com/c/rock-paper-scissors/code) was an extension of the basic rock-paper-scissors game (known as roshambo in some parts of the world): instead of the usual “best of 3” score, we use “best of 1,000.”

We will describe two possible approaches to the problem: one rooted in the game-theoretic approach, and the other more focused on the algorithmic side.

We begin...

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