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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

Netiquette

Anybody who has been online for longer than 15 minutes knows this: during a discussion, no matter how innocent the topic, there is always a possibility that people will become emotional, and a conversation will leave the civilized parts of the spectrum. Kaggle is no exception to the rule, so the community has guidelines for appropriate conduct: https://www.kaggle.com/community-guidelines.

Those apply not just to discussions, but also to Notebooks and other forms of communication. The main points you should keep in mind when interacting on Kaggle are:

  • Don’t slip into what Scott Adams calls the mind-reading illusion: Kaggle is an extremely diverse community of people from all over the world (for many of them, English is not their first language), so maintaining nuance is a massive challenge. Don’t make assumptions and try to clarify whenever possible.
  • Do not make things personal; Godwin’s law is there for a reason. In particular,...
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