Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Advanced Search Sign In Start Free Trial

Add to playlist

Create a Playlist

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

Developing Kaggle Notebooks

By : Gabriel Preda
5 (29)
Buy this Book
close
close
Developing Kaggle Notebooks

Developing Kaggle Notebooks

5 (29)
By: Gabriel Preda
Buy this Book

Overview of this book

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.
Table of Contents (14 chapters)
close
close
close
Preface
Icon
Preface
Icon
Who this book is for
Icon
What this book covers
Icon
To get the most out of this book
Icon
Get in touch
Free Chapter
1
Introducing Kaggle and Its Basic Functions
chevron up
Icon
Introducing Kaggle and Its Basic Functions
Icon
The Kaggle platform
Icon
Kaggle Competitions
Icon
Kaggle Datasets
Icon
Kaggle Code
Icon
Kaggle Discussions
Icon
Kaggle Learn
Icon
Kaggle Models
Icon
Summary
2
Getting Ready for Your Kaggle Environment
Icon
Getting Ready for Your Kaggle Environment
Icon
What is a Kaggle Notebook?
Icon
How to create notebooks
Icon
Exploring notebook capabilities
Icon
Using the Kaggle API to create, update, download, and monitor your notebooks
Icon
Summary
3
Starting Our Travel – Surviving the Titanic Disaster
Icon
Starting Our Travel – Surviving the Titanic Disaster
Icon
A closer look at the Titanic
Icon
Conducting data inspection
Icon
Performing univariate analysis
Icon
Performing multivariate analysis
Icon
Extracting meaningful information from passenger names
Icon
Creating a dashboard showing multiple plots
Icon
Building a baseline model
Icon
Summary
Icon
References
4
Take a Break and Have a Beer or Coffee in London
Icon
Take a Break and Have a Beer or Coffee in London
Icon
Pubs in England
Icon
Starbucks around the world
Icon
Pubs and Starbucks in London
Icon
Summary
Icon
References
5
Get Back to Work and Optimize Microloans for Developing Countries
Icon
Get Back to Work and Optimize Microloans for Developing Countries
Icon
Introducing the Kiva analytics competition
Icon
More data, more insights – analyzing the Kiva data competition
Icon
Telling a different story from a different dataset
Icon
Summary
Icon
References
6
Can You Predict Bee Subspecies?
Icon
Can You Predict Bee Subspecies?
Icon
Data exploration
Icon
Subspecies classification
Icon
Summary
Icon
References
7
Text Analysis Is All You Need
Icon
Text Analysis Is All You Need
Icon
What is in the data?
Icon
Analyzing the comments text
Icon
Preparing the model
Icon
Building a baseline model
Icon
Transformer-based solution
Icon
Summary
Icon
References
8
Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
Icon
Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
Icon
Introducing the LANL Earthquake Prediction competition
Icon
Formats for signal data
Icon
Exploring our competition data
Icon
Feature engineering
Icon
Building a baseline model
Icon
Summary
Icon
References
9
Can You Find Out Which Movie Is a Deepfake?
Icon
Can You Find Out Which Movie Is a Deepfake?
Icon
Introducing the competition
Icon
Introducing competition utility scripts
Icon
Metadata exploration
Icon
Video data exploration
Icon
Summary
Icon
References
10
Unleash the Power of Generative AI with Kaggle Models
Icon
Unleash the Power of Generative AI with Kaggle Models
Icon
Introducing Kaggle Models
Icon
Prompting a foundation model
Icon
Building a multi-task application with Langchain
Icon
Code generation with Kaggle Models
Icon
Creating a RAG system
Icon
Summary
Icon
References
11
Closing Our Journey: How to Stay Relevant and on Top
Icon
Closing Our Journey: How to Stay Relevant and on Top
Icon
Learn from the best: observe successful Grandmasters
Icon
Revisit and refine your work periodically
Icon
Recognize other’s contributions, and add your personal touch
Icon
Be quick: don’t wait for perfection
Icon
Be generous: share your knowledge
Icon
Step outside your comfort zone
Icon
Be grateful
Icon
Summary
Icon
References
12
Other Books You May Enjoy
Icon
Other Books You May Enjoy
13
Index
Icon
Index

Introducing Kaggle and Its Basic Functions

Kaggle is currently the main platform for competitive predictive modeling. Here, those who are passionate about machine learning, both experts and beginners, have a collaborative and competitive environment to learn, win recognition, share knowledge, and give back to the community. The company was launched in 2010, offering only machine learning competitions. Currently, it is a data platform that includes sections titled Competitions, Datasets, Code, Discussions, Learn, and, most recently, Models.

In 2011, Kaggle went through an investment round, valuing the company above $25 million. In 2017, it was acquired by Google (now Alphabet Inc.), becoming associated with Google Cloud. The most notable key persons from Kaggle are co-founders Anthony Goldbloom (long-time CEO until 2022) and Ben Hammer (CTO). Recently, D. Sculley, the legendary Google engineer, became Kaggle’s new CEO, after Anthony Goldbloom stepped down to become involved in the development of a new start-up.

In this first chapter, we’ll explore the main sections that the Kaggle platform offers its members. We will also learn how to create an account, how the platform is organized, and what its main sections are. In short, this chapter will cover the following topics:

  • The Kaggle platform
  • Kaggle Competitions
  • Kaggle Datasets
  • Kaggle Code
  • Kaggle Discussions
  • Kaggle Learn
  • Kaggle Models

If you are familiar with the Kaggle platform, you probably know about these features already. You can choose to continue reading the following sections to refresh your knowledge about the platform or you can skip them and go directly to the next chapter.

End of Section 1
Next Section

Create a Note

Modal Close icon
You need to login to use this feature.
notes
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

Delete Note

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

Confirmation

Modal Close icon
claim successful
Order Page Read Now

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