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Developing Kaggle Notebooks

You're reading from   Developing Kaggle Notebooks Pave your way to becoming a Kaggle Notebooks Grandmaster

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781805128519
Length 370 pages
Edition 1st Edition
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Author (1):
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Gabriel Preda Gabriel Preda
Author Profile Icon Gabriel Preda
Gabriel Preda
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Table of Contents (14) Chapters Close

Preface 1. Introducing Kaggle and Its Basic Functions FREE CHAPTER 2. Getting Ready for Your Kaggle Environment 3. Starting Our Travel – Surviving the Titanic Disaster 4. Take a Break and Have a Beer or Coffee in London 5. Get Back to Work and Optimize Microloans for Developing Countries 6. Can You Predict Bee Subspecies? 7. Text Analysis Is All You Need 8. Analyzing Acoustic Signals to Predict the Next Simulated Earthquake 9. Can You Find Out Which Movie Is a Deepfake? 10. Unleash the Power of Generative AI with Kaggle Models 11. Closing Our Journey: How to Stay Relevant and on Top 12. Other Books You May Enjoy
13. Index

Analyzing Acoustic Signals to Predict the Next Simulated Earthquake

In the previous chapters, we explored basic table-formatted data, covering categories like categorical, ordinal, and numerical data, as well as text, geographical coordinates, and imagery. The current chapter shifts our focus to a different data category, specifically, simulated or experimental signal data. This data type often appears in a range of formats beyond the standard CSV file format.

Our primary case study will be data from the LANL Earthquake Prediction Kaggle competition (see Reference 1). I contributed to this competition with a widely recognized and frequently forked notebook titled LANL Earthquake EDA and Prediction (see Reference 2), which will serve as the foundational resource for this chapter’s principal notebook. We’ll then delve into feature engineering, employing a variety of signal analysis techniques vital for developing a predictive model for the competition. Our goal will...

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