THE KAGGLE WORKBOOK self-learning exercises and valuable insights for Kaggle data science competitions /

Move up the Kaggle leaderboards and supercharge your data science and machine learning career by analyzing famous competitions and working through exercises. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Challenge yourself to start thinking like a Kaggle Gran...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Banachewicz, Konrad (Autor), Massaron, Luca (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing Ltd., [2023]
Temas:
Machine learning > Problems, exercises, etc.
Big data > Problems, exercises, etc.
Big data.
Machine learning.
Electronic books.
Problems and exercises.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Cover
  • Copyright
  • Table of Contents
  • Preface
  • Chapter 1: The Most Renowned Tabular Competition
  • Porto Seguro's Safe Driver Prediction
  • Understanding the competition and the data
  • Understanding the evaluation metric
  • Examining the top solution ideas from Michael Jahrer
  • Building a LightGBM submission
  • Setting up a denoising autoencoder and a DNN
  • Ensembling the results
  • Summary
  • Chapter 2: The Makridakis Competitions
  • M5 on Kaggle for Accuracy and Uncertainty
  • Understanding the competition and the data
  • Understanding the Evaluation Metric
  • Examining the 4th place solution's ideas from Monsaraida
  • Computing predictions for specific dates and time horizons
  • Assembling public and private predictions
  • Summary
  • Chapter 3: Vision Competition: Cassava Leaf Disease Competition
  • Understanding the data and metrics
  • Building a baseline model
  • Learning from top solutions
  • Pretraining
  • Test time augmentation
  • Transformers
  • Ensembling
  • A complete solution
  • Summary
  • Chapter 4: NLP Competition
  • Google Quest Q&A Labeling
  • The baseline solution
  • Learning from top solutions
  • Summary
  • Packt page
  • Other Books You May Enjoy
  • Index

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