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NVTabular v0.3.0 (Unreleased)

Improvements

  • Add MultiHot categorical support for both preprocessing and dataloading
  • Add support for pretrained embeddings to the dataloaders
  • Add a Recsys2020 competition example notebook
  • Add ability to automatically map tensorflow feature columns to a NVTabular workflow
  • Multi-Node support

NVTabular v0.2.0 (10 September 2020)

Improvements

  • Add Multi-GPU support using Dask-cuDF
  • Add support for reading datasets from S3, GCS and HDFS
  • Add 11 new operators: ColumnSimilarity, Dropna, Filter, FillMedian, HashBucket, JoinGroupBy, JoinExternal, LambdaOp, NormalizeMinMax, TargetEncoding and DifferenceLag
  • Add HugeCTR integration and an example notebook showing an end to end workflow
  • Signicantly faster dataloaders featuring a unified backend between TensorFlow and PyTorch

NVTabular v0.1.1 (3 June 2020)

Improvements

  • Switch to using the release version of cudf 0.14

Bug Fixes

  • Fix PyTorch dataloader for compatability with deep learning examples
  • Fix FillMissing operator with constant fill
  • Fix missing yaml dependency on conda install
  • Fix get_emb_sz off-by-one error

NVTabular v0.1.0 - (13 May 2020)

  • Initial public release of NVTabular