v0.1.3 (2020-10-16)

This version includes several minor improvements to the PAR model and the
way the sequences are generated:

• Sequences can now be generated without dropping the sequence index.
• The PAR model learns the min and max length of the sequence from the input data.
• NaN values are properly supported for both categorical and numerical columns.
• NaN values are generated for numerical columns only if there were NaNs in the input data.
• Constant columns can now be modeled.

v0.1.2 (2020-09-15)

Add BasicGAN Model and additional benchmarking results.

v0.1.1 (2020-08-15)

This release includes a few new features to make DeepEcho work on more types of datasets
as well as to making it easier to add new datasets to the benchmarking framework.

• Add segment_size and sequence_index arguments to fit method.
• Add sequence_length as an optional argument to sample and sample_sequence methods.
• Update the Dataset storage format to add sequence_index and versioning.
• Separate the sequence assembling process in its own deepecho.sequences module.
• Add function make_dataset to create a dataset from a dataframe and just a few column names.
• Add notebook tutorial to show how to create a datasets and use them.

v0.1.0 (2020-08-11)

First public release.

Included Features:

• PARModel
• Demo dataset and tutorials
• Benchmarking Framework
• Support and instructions for benchmarking on a Kubernetes cluster.

v0.0.2 - 2020-07-17

First fully usable release.

Included Features:

• PARModel
• Demo dataset and tutorials
• Benchmarking Framework
• Support and instructions for benchmarking on a Kubernetes cluster.

v0.0.1

First release to PyPI.