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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

Kaggle Discussions

Kaggle Discussions are either associated with other sections or independent. Competitions and Datasets both have Discussions sections. For Code, there is a Comments section. In the Discussions section, you can add topics for discussion or comments under a topic. For Code, you can add comments. Besides these contexts, you can add topics or comments under Forums, or you can follow discussions under Discussions from across the Kaggle section. Forums are grouped by subjects, and you can choose between General, Getting Started, Product Feedback, Questions & Answers, and Competition Hosting. Under Discussions, across Kaggle, you can search the content or focus on a tagged subtopic, like Your Activity, Bookmarks, Beginner, Data Visualization, Computer Vision, NLP, Neural Networks, and more.

Discussions also has a progression system and you can get ranking points and medals by accumulating upvotes. Unlike the other sections in which you can get upvotes, in Discussions, you can get downvotes as well. Ranking points can vanish over time and upvotes will count for medals only if from non-Novices and if new. You cannot upvote yourself in Discussions.

Performance tiers in Discussions start with Expert, and you can get this tier by accumulating 50 bronze medals. To get to the next tier, Master, you need 50 silver medals and 200 medals in total, and to reach the Grandmaster tier, you need 50 gold medals and 500 medals in total. Medals are easy to obtain in Discussions compared with other sections; you only need 1 upvote for a bronze medal, 5 upvotes for a silver medal, and a total of 10 upvotes for a gold medal. As with the Datasets and Code cases, the votes are not permanent. Users can decide to retract their upvotes; therefore, you can lose some of your upvotes, ranking points, medals, or even performance tier status.

At the time of writing this book, there were 62 Grandmasters in Discussions and 103 Masters.

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