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Key benefits

Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models

Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound

Improve the style and readability of your Notebooks, making them more impactful and compelling

Description

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.

Who is this book for?

This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any background Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings Professionals who already use Kaggle for learning and competing

What you will learn

Approach a dataset or competition to perform data analysis via a notebook

Learn data ingestion and address issues arising with the ingested data

Structure your code using reusable components

Analyze in depth both small and large datasets of various types

Distinguish yourself from the crowd with the content of your analysis

Enhance your notebook style with a color scheme and other visual effects

Captivate your audience with data and compelling storytelling techniques

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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K Kapoor Mar 15, 2024

Developing Kaggle Notebooks by Gabriel Preda stands out for its comprehensive approach to data science and Machine Learning on Kaggle. The book delves into various ML projects, explores diverse data types, and provides valuable hands-on projects. This practical learning experience caters to both beginners and experienced professionals seeking to enhance their skills. with a systematically crafted book to excel in developing notebooks.Gabriel's expertise and knowledge shine through in the book as he simplifies complex concepts, making it an exceptional resource for anyone aspiring to excel in data science on Kaggle and otherwise too.I want to thank Gabriel and Packt Publishing for their valuable contribution to the community with this exceptional addition.

Amazon Verified review

Lakshit Jan 15, 2024

I personally use Kaggle on my Chromebook for side projects, taking the burden away from my 4-year-old personal laptop. Even though I am far from a Kaggle grandmaster, I use Kaggle frequently for my side projects and haven't participated in any live competitions, despite considering it many times.This book is ideal for aspiring data scientists with intermediate ML expertise. It takes the approach of teaching by example (in my opinion all good books must do this) and touches on Kaggle's abilities to be an incredible resource for practicing ML using datasets, competitions, discussions and learning concepts.The major discussion is through examples, starting from the "hello world" of ML – the Titanic problem – and progresses to NLP problems.Through each chapter's accompanying code and explanations, you can understand the best practices the author suggests for EDA, feature engineering, and deep diving into the data to tell the story we want, rather than building a story about full comprehensive data analysis. After all, the author suggests that his winning Kaggle Grandmaster status was also because of adhering to select best practices he writes about in the book.Definitely great for people who are existing Kaggle users and want to level up, refine their presentation skills, and create powerful narratives with data.

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Teresia Feb 01, 2024

I recently had the pleasure of reading "Developing Kaggle Notebooks" by Gabriel and it exceeded my expectations in every way. The book masterfully combines the intricacies of Kaggle notebooks with a simplified explanation of machine learning concepts, making it an invaluable resource for both beginners and seasoned practitioners.What sets this book apart is its practical approach – allowing readers to code along and create notebooks in real-time. This hands-on experience enhances the learning process, making complex concepts more accessible. The author's expertise shines through, delivering a comprehensive guide that is both insightful and user-friendly.I highly recommend "Developing Kaggle Notebooks" to anyone seeking mastery in machine learning and Kaggle competitions. It's a must-read for those who want to deepen their understanding and practical skills in the field.This book is also written by a 3x Kaggle Grandmaster, what a wonderful way to learn from the experts themselves.

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Cristina Radu Jan 18, 2024

This book is amazing, it takes you from the basics of analysis of tabular data to performing geospatial analysis to text analysis and image, video and signal analysis. It teaches you not only how to analyse data but also how to structure your code to create and iteratively refine a model - to create a competition submission. Additionally, it shows how to create a story with your data and how to build high impact Notebooks on Kaggle. In one of the last chapters explores how you can prototype generative AI applications using resources on Kaggle, especially the Large Language Models available through Kaggle Models. Highly recommended for the absolute beginners as well as more advanced users.

Amazon Verified review

Suzy Jan 22, 2024

Listen, the tldr is that this is an amazing resource that everyone in this field can benefit from. Do yourself a favour and get it, learn and be better. Gabriel has outdone himself with this … I wish I’d had a resource like this when I started out, but even still… I was still learning things constantly throughout my read.As a two-time Kaggle Grandmaster, diving into "Developing Kaggle Notebooks" felt like hitting a goldmine. The book nails the essence of what it takes to excel in Kaggle and in the wider data science arena.I LOVED how it guides you through the data science process, echoing the real challenges and triumphs we face in competitions. The focus on crafting notebooks that are not just analytically sound but also visually striking is spot on. It's something I've always championed – your analysis needs to speak clearly and compellingly, and this book gets that right.The practical tips on handling different data types and leveraging Kaggle's Utility Scripts are exactly what you need to up your efficiency game. And the bit on generative AI? It’s like they’re reading our minds, staying ahead of the curve in a field that never stops evolving.In a nutshell, "Developing Kaggle Notebooks" is a must-read. Whether you're starting out or looking to sharpen your skills, this book has got you covered, blending deep insights with actionable advice. It's a solid companion for anyone serious about making their mark in data science.Congratulations on the excellent work Gabriel.CHEERS, and good luck on your journey!Darien Schettler

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

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