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Developing Kaggle Notebooks

You're reading from Developing Kaggle Notebooks

Product type Book

Published in Dec 2023

Publisher Packt

ISBN-13 9781805128519

Pages 370 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Gabriel Preda

Table of Contents (14) Chapters

Preface

1. Introducing Kaggle and Its Basic Functions

2. Getting Ready for Your Kaggle Environment

3. Starting Our Travel – Surviving the Titanic Disaster

4. Take a Break and Have a Beer or Coffee in London

5. Get Back to Work and Optimize Microloans for Developing Countries

6. Can You Predict Bee Subspecies?

7. Text Analysis Is All You Need

8. Analyzing Acoustic Signals to Predict the Next Simulated Earthquake

9. Can You Find Out Which Movie Is a Deepfake?

10. Unleash the Power of Generative AI with Kaggle Models

11. Closing Our Journey: How to Stay Relevant and on Top

12. Other Books You May Enjoy

13. Index

The data

The competition requires the participants to identify or collect relevant data, besides the data provided by organizers. This includes loans information, Kiva global multidimensional poverty index (MPI) by region and location, loan theme and loan themes by region. The loans information include an unique id, loan theme id, loan theme type, local financial organization partner id, funded amount (how much Kiva provided to the local partner), loan amount (how much the local partner disbursed to the borrower), the activity of the borrower, sector, use of the loan, country code, country name, region, currency, posted time, disbursed time, funded time, duration in time for which the loan was disbursed, the total number of lenders that contributed to a loan, gender of borrowers, and repayment interval. Kiva MPI by region and location include region or country name, ISO-3 code for the country, region, world region, MPI value and the geolocation (latitude and longitude) of the current...

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Authors (1)

Gabriel Preda

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.

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