Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.

For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable.

Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.

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Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.

For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable.

Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.

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Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

Developing Kaggle Notebooks: Pave your way to becoming a Kaggle Notebooks Grandmaster

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Overview

Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.

For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable.

Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.


Product Details

ISBN-13: 9781805125716
Publisher: Packt Publishing
Publication date: 12/27/2023
Sold by: Barnes & Noble
Format: eBook
Pages: 370
File size: 32 MB
Note: This product may take a few minutes to download.

About the Author

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.

Table of Contents

Table of Contents
  1. Introducing Kaggle and Its Basic Functions
  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
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