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Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact
Leverage the power of Generative AI with Kaggle Models
Purchase of the print or Kindle book includes a free PDF eBook
Key FeaturesMaster the basics of data ingestion, cleaning, exploration, and prepare to build baseline modelsWork robustly with any type, modality, and size of data, be it tabular, text, image, video, or soundImprove the style and readability of your Notebooks, making them more impactful and compellingBook 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.
What you will learnApproach a dataset or competition to perform data analysis via a notebookLearn data ingestion and address issues arising with the ingested dataStructure your code using reusable componentsAnalyze in depth both small and large datasets of various typesDistinguish yourself from the crowd with the content of your analysisEnhance your notebook style with a color scheme and other visual effectsCaptivate your audience with data and compelling storytelling techniquesWho this book is 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
Table of ContentsIntroducing Kaggle and Its Basic FunctionsGetting Ready for Your Kaggle EnvironmentStarting Our Travel – Surviving the Titanic DisasterTake a Break and Have a Beer or Coffee in LondonGet Back to Work and Optimize Microloans for Developing CountriesCan You Predict Bee Subspecies?Text Analysis Is All You NeedAnalyzing Acoustic Signals to Predict the Next Simulated EarthquakeCan You Find Out Which Movie Is a Deepfake?Unleash the Power of Generative AI with Kaggle ModelsClosing Our Journey: How to Stay Relevant and on Top
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Publisher : Packt Publishing (December 27, 2023)
Language : English
Paperback : 370 pages
ISBN-10 : 1805128515
ISBN-13 : 978-1805128519
Item Weight : 1.43 pounds
Dimensions : 9.25 x 7.52 x 0.77 inches
Customers say
Customers find the book provides an expert guide to data analysis. It teaches them how to develop data analysis notebooks on Kaggle and explore a wide array of datasets. The book offers valuable insights on handling various data types, including tabular data, text, images, video, and text. Readers appreciate the visual style and custom graphical elements used to improve notebook presentation. Overall, it’s a good resource for learning hands-on how to develop data analysis Notebooks on Kaggle.
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