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Developing Kaggle Notebooks

Developing Kaggle Notebooks

By : Gabriel Preda
5 (29)
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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)
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Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Introducing Kaggle and Its Basic Functions
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Introducing Kaggle and Its Basic Functions
The Kaggle platform
Kaggle Competitions
Kaggle Datasets
Kaggle Code
Kaggle Discussions
Kaggle Learn
Kaggle Models
Summary
2
Getting Ready for Your Kaggle Environment
Getting Ready for Your Kaggle Environment
What is a Kaggle Notebook?
How to create notebooks
Exploring notebook capabilities
Using the Kaggle API to create, update, download, and monitor your notebooks
Summary
3
Starting Our Travel – Surviving the Titanic Disaster
Starting Our Travel – Surviving the Titanic Disaster
A closer look at the Titanic
Conducting data inspection
Performing univariate analysis
Performing multivariate analysis
Extracting meaningful information from passenger names
Creating a dashboard showing multiple plots
Building a baseline model
Summary
References
4
Take a Break and Have a Beer or Coffee in London
Take a Break and Have a Beer or Coffee in London
Pubs in England
Starbucks around the world
Pubs and Starbucks in London
Summary
References
5
Get Back to Work and Optimize Microloans for Developing Countries
Get Back to Work and Optimize Microloans for Developing Countries
Introducing the Kiva analytics competition
More data, more insights – analyzing the Kiva data competition
Telling a different story from a different dataset
Summary
References
6
Can You Predict Bee Subspecies?
Can You Predict Bee Subspecies?
Data exploration
Subspecies classification
Summary
References
7
Text Analysis Is All You Need
Text Analysis Is All You Need
What is in the data?
Analyzing the comments text
Preparing the model
Building a baseline model
Transformer-based solution
Summary
References
8
Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
Introducing the LANL Earthquake Prediction competition
Formats for signal data
Exploring our competition data
Feature engineering
Building a baseline model
Summary
References
9
Can You Find Out Which Movie Is a Deepfake?
Can You Find Out Which Movie Is a Deepfake?
Introducing the competition
Introducing competition utility scripts
Metadata exploration
Video data exploration
Summary
References
10
Unleash the Power of Generative AI with Kaggle Models
Unleash the Power of Generative AI with Kaggle Models
Introducing Kaggle Models
Prompting a foundation model
Building a multi-task application with Langchain
Code generation with Kaggle Models
Creating a RAG system
Summary
References
11
Closing Our Journey: How to Stay Relevant and on Top
Closing Our Journey: How to Stay Relevant and on Top
Learn from the best: observe successful Grandmasters
Revisit and refine your work periodically
Recognize other’s contributions, and add your personal touch
Be quick: don’t wait for perfection
Be generous: share your knowledge
Step outside your comfort zone
Be grateful
Summary
References
12
Other Books You May Enjoy
Other Books You May Enjoy
13
Index
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
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