Hyperparameter Tuning for ML and DL with R

Eva Bartz, Thomas Bartz-Beielstein, Martin Zaefferer, Olaf Mersmann ★ 4.60 (11 reviews) Mid-Range

Price tier: Mid-Range
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Hyperparameter Tuning for Machine and Deep Learning with R: A Practical Guide

Practical guide for tuning hyperparameters in machine and deep learning using R. improves model performance with actionable methods. customer insight: none

Highlights

  • dual focus on ML and DL in R
  • practical, actionable methods
  • clear guidance for performance gains

Pros

  • practical guidance for hyperparameter tuning
  • covers both ML and DL with R
  • clear, actionable techniques
  • suitable for researchers and practitioners

Cons

  • no customer insights provided
  • no features listed
  • brand and author details not product-specific

Best For

  • tuning hyperparameters for ML models
  • tuning hyperparameters for deep learning models
  • experimental setup in R for ML/DL
  • improving model performance through tuning
  • reproducible tuning workflows
  • academic research in hyperparameter optimization

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