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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

Index

A

aggregated functions

features derived, calculating from 248-252

Audio Video Interleave (AVI) 267

B

baseline model

building 64-66, 223-227, 257-262

Basic Linear Algebra Subprograms (BLAS) 246, 247

bee subspecies, classification 174

baseline model, building 177-182

data augmentation 176, 177

data, splitting 175, 176

model, refining iteratively 182-186

bee subspecies, data exploration 154

data, grouping in single dataset by locations 159-161

date and time 162-164

image data, exploring 156-159

images, with bees carrying pollen and not carrying pollen 172

quality checks 154, 155

subspecies 164-169

Black, Indigenous, and People of Color (BIPOC) 13

borrower demographic 125-128

C

CascadeObjectDetector class 271

Central Processing Unit (CPU) 24

classic Short-Term Average/Long-Term Average (STA/LTA) 244-246

code generation

with Kaggle Models 311, 312

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Developing Kaggle Notebooks

Published in: Dec 2023 Publisher: Packt ISBN-13: 9781805128519

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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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