Book Image

The Kaggle Book

By : Konrad Banachewicz, Luca Massaron
5 (2)
Book Image

The Kaggle Book

5 (2)
By: Konrad Banachewicz, Luca Massaron

Overview of this book

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you’ll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won’t easily find elsewhere, and the knowledge they’ve accumulated along the way. As well as Kaggle-specific tips, you’ll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You’ll design better validation schemes and work more comfortably with different evaluation metrics. Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you. Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!
Table of Contents (20 chapters)
Preface
1
Part I: Introduction to Competitions
6
Part II: Sharpening Your Skills for Competitions
15
Part III: Leveraging Competitions for Your Career
18
Other Books You May Enjoy
19
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 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 very broad and encompasses very popular topics such as chatbots and machine translation, in this chapter we will focus on specific subsets that Kaggle contests frequently deal with.

Sentiment analysis as a simple classification problem is extremely popular and discussed all over, so we’ll begin with a somewhat more interesting variation on the problem: 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, which is a topic that receives significantly less attention than...