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Developing Kaggle Notebooks

Developing Kaggle Notebooks

By : Gabriel Preda
5 (29)
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Developing Kaggle Notebooks

Developing Kaggle Notebooks

5 (29)
By: Gabriel Preda

Overview of this book

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.
Table of Contents (14 chapters)
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12
Other Books You May Enjoy
13
Index

Recognize other’s contributions, and add your personal touch

To elevate your notebooks on platforms like Kaggle, it’s crucial to engage in a continuous process of improvement and innovation, drawing on both community feedback and the work of others. Regularly revisiting and updating your notebooks based on constructive comments demonstrates a commitment to excellence. You can also look at what others have done. Just forking their work will not bring you too many upvotes. However, if you start from other users’ work and bring new insights by expanding their observations and improving on a visualization or interpretation of the results, it can help you to rise in the ranks.

Moreover, it is extremely important to correctly state when you are starting from somebody’s else work, and be clear on your own contribution. If you want to combine your notebook ideas from various sources, it is recommended to fork the one from which you borrow the most content....

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