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New features and improvements

  • Updated to tensorflow 1.13.1 and spacy 2.1 (this also makes Ludwig compatible with Python 3.7)
  • Added an initial integration with
  • Added support for text preprocessing of additional languages: Italian, Spanish, German, French, Portuguese, Dutch, Greek and Multi-language (Fature Request #251).
  • Added skip_save_progress, skip_save_model and skip_save_log parameters
  • Improved the default parameters of the image feature (this may make previously trained models including image features not compatible. If that is the case retrain your model)
  • Added PassthroughEncoder
  • Added eval_batch_size parameter
  • Added sanity checks for model definitions, with improved error messages
  • Add Dockerfile for running Ludwig on a CPU
  • Added clip parameter to numerical output features
  • Added a full MNIST training example, a fraud detection example and a more complex regression example on fuel consumption

Bug fixes

  • Fix issue #56: removing just keys that exist in dataset when when replacing text feature names concatenating their level
  • Fix issue #46 #144: Solved Mac OS X mpl.use('TkAgg') use
  • Fix issue #74: Call subprocess within try except
  • Fix issue #81: Opens a file before calling yaml.load()
  • Fix issue #90: Forcing csv writer to write utf-8 encoded files
  • Fix issue #120: Missing sgd (and synonyms) key in optimizers default
  • Fix issue #64: Fix for files with capitalized extensions
  • Fix issue #121: Typo bucketin_field to bucketing_field
  • Fix training when validation or test cvs are provided separately
  • Fix issue #112: dataframe_df may not have a csv attribute
  • Fix missing checks if dataset is None in and
  • Fix error measure aggregation and default value
  • Fix image interpolation
  • Fix preprocessing_defaults error in
  • Fix text output features populate_defaults() and update_model_definition_with_metadata()
  • Fix in timeseires placeholder datatype
  • Moved image preprocessing params to preprocessing section (this may make previously trained models including image features not compatible. If that is the case retrain your model)
  • Fix warmup learning rate function for distributed training
  • Fix issue #214: replace_text_feature_level usage in
  • Fix issue #214: replaced SPACE_PUNCTUATION_REGEX
  • Fix issue #229 #100: solved missing hdf5 / csv file reference
  • Fix issue #222: incorrect logging in read_csv
  • Fix issue #194: Renaming class_distance to class_similarities and several bugfixes regarding class_similarities, class_weights and their interaction at model building time
  • Fix issue #100 #225: solves image prediction issues
  • Fix issue #98: solves dealing with images with different numbers of channels, including transparencies
  • Fix unwanted creation of hdf5 files when running ludwig.predict on images
  • And few more minor fixes


Thanks to all our amazing contributors (some of your PRs were not merged, but we used some of their code in our commits, so thank you anyway!):
@dsblank @MariusDanner @BenMacKenzie @Barathwaja @gabefair @kevinqz @yantsey @jontonsoup4 @Praneet460 @DakshMiglani @syeef @Tejaf @rolisz @JakeConnors376W @AndyZZH @us @0xflotus @laserbeam3 @krychu @dettmering @bbrodsky @c-m-hunt @C0deFxxker @hemchander23 @Shivam-Beeyani @yashrajbharti @rbramwell @emushtaq @EBazarov @graytowne @jovilius @ivanhe @philippgille @floscha

Assets 2

@w4nderlust w4nderlust released this Feb 11, 2019 · 176 commits to master since this release

This is the first public release of Ludwig

Assets 2
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