Key features

Integrated tools for evaluation

Data exploration and feature engineering

  • Ability to compare statistics between two datasets
  • Sanity checks
  • Ability to detect skew between train and eval
  • Automated and distributed PCA

Smart splitting into train-eval

  • Ability to tag data points and split according to groups
  • Comparison of how splitting data affected experiments
  • In-depth evaluation with slicing metrics

Time-series support

  • Custom split on timestamped data points
  • Fundamental preprocessing steps on sequences such as resampling or filling
  • Automated visualization over time

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