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  • Book Overview & Buying The Kaggle Book
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The Kaggle Book

The Kaggle Book - Second Edition

By : Luca Massaron, Bojan Tunguz, Konrad Banachewicz
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The Kaggle Book

The Kaggle Book

By: Luca Massaron, Bojan Tunguz, Konrad Banachewicz

Overview of this book

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. Join our Discord community of over 1,000 members to learn, share, and grow together!
Table of Contents (23 chapters)
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1
Part 1: Your Kaggle Launchpad: Mastering the Essentials
7
Part 2: Elevating Your Game: Advanced Techniques for Competitive Success
17
Part 3: Kaggle for Your Career: Building Your Profile and Finding Opportunities
21
Other Books You May Enjoy
22
Index

Modeling for NLP

Natural language processing (NLP) is a field operating at the intersection of linguistics, computer science, and AI. Its primary focus is on algorithms to process and analyze large amounts of natural language data. Over the last few years, it has become an increasingly popular topic of Kaggle competitions. While the domain itself is vast and encompasses very popular topics, such as chatbots and machine translation, this chapter will focus on specific subsets that Kaggle contests frequently address.

Sentiment analysis, as a simple classification problem, is extremely popular and widely discussed, so we’ll begin with a somewhat more interesting variation on the issue: identifying sentiment-supporting phrases in a tweet. We’ll proceed to describe an example solution to the problem of open-domain question-answering and conclude with a section on augmentation for NLP problems, a topic that receives significantly less attention than its computer vision...

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The Kaggle Book
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