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The Kaggle Book 2nd Edition by Luca Massaron

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  • 2,950.00
  • 13%
  • 2,950.00
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Highlights:

BLACK & WHITE Final Release Version
Language ‏ : ‎ English
Paperback, 709 Pages, Edition 2026
A+ PDF Printed On Demand Book!
Local Printed Book!
Delivery All Over Pakistan Charges Will Apply.
Due to constant currency fluctuation, prices are subject to change with or without notice.

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Description

The Kaggle Book: Master data science competitions with machine learning, GenAI, and LLMs, 2nd Edition

Luca Massaron, Bojan Tunguz, Konrad Banachewicz

Stay one step ahead of your competitors with proven tips, strategies, and insights from over 30 Kaggle Masters and Grandmasters and become a better data scientist. This new edition features updated content and new chapters on Kaggle Models, time series, and Generative AI competitions.

Key Features

-Learn how Kaggle works to make the most of every competition with winning strategies from 30+ expert Kagglers

-Sharpen your modeling skills with feature engineering, adversarial validation, gradient boosting, tabular deep learning, ensembling, and AutoML

-Master data handling techniques for smarter modeling and parameter tuning

Book Description

Kaggle has become the proving ground for millions of data enthusiasts worldwide, offering what no classroom tutorial can match: battle-tested skills built through real-world challenges and the hands-on experience that employers seek. Every competition sharpens your data analysis skills, expands your network within the data scientist community, and gives compelling proof of expertise to unlock career opportunities. The first book of its kind, The Kaggle Book brings together everything you need to excel in competitions, data science projects, and beyond. This new edition includes fresh content and new chapters on Kaggle Models, time series, and Generative AI competitions, with three Kaggle Grandmasters guiding you through modeling strategies and sharing hard-earned insights accumulated over years of competition. The book extends far past competition tactics, revealing techniques for tackling image, tabular, and textual data as well as reinforcement learning tasks. You’ll also discover tips for designing better validation schemes and working confidently with both standard and unconventional evaluation metrics. Whether you want to climb the Kaggle leaderboard, accelerate your data science career, or improve the accuracy of your models, this book is for you.

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