Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying The Kaggle Book
  • Table Of Contents Toc
  • Feedback & Rating feedback
The Kaggle Book

The Kaggle Book

By : Konrad Banachewicz, Luca Massaron
4.1 (34)
close
close
The Kaggle Book

The Kaggle Book

4.1 (34)
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)
close
close
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

Summary

In this chapter, we gave you an overview of the most important topics related to computer vision from a Kaggle competition angle. We introduced augmentations, an important class of techniques used for extending the generalization capabilities of an algorithm, and followed by demonstrating end-to-end pipelines for three of the most frequent problems: image classification, object detection, and semantic segmentation.

In the next chapter, we switch our attention to natural language processing, another extremely broad and popular category of problems.

Join our book’s Discord space

Join the book’s Discord workspace for a monthly Ask me Anything session with the authors:

https://packt.link/KaggleDiscord

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY