Changes in version 0.3.0                        

Architecture Change:

  - moved all Amazon machine learning framework classes to
    sagemaker.mlframework
  - moved clarify classes and method to sagemaker.common ** NOTE:** this
    changes reduce package overall size from 5Mb to 3.7Mb align to CRAN
    package size limitations.

                        Changes in version 0.2.4                        

Bug Fix:

  - Class HyperparameterTuner correctly validates hyper parameters
  - Correctly pass static hyperparameters

Feature:

  - Class HyperparameterTuner create method is now callable at
    R6ClassGenerator level. To help mimic python equivalent.

                        Changes in version 0.2.3                        

Bug Fix:

  - correctly parse parameters class

Minor:

  - Add .module field to estimator classes to minic python
    cls.__module__

                        Changes in version 0.2.2                        

Bug Fix:

  - allow container_log_level to pass any string instead of restricting
    to logging levels.

Minor:

  - explicitly reference sagemaker.core functions to help with mock
    functionality

                        Changes in version 0.2.1                        

Bug Fix:

  - Ensure deserializer classes correctly parse raw vectors as expected.

                        Changes in version 0.2.0                        

Feature:

  - Add SparseMatrixSerializer serialize class
  - Allow all serializer classes read from data in from file.
  - LibSVMSerializer class now uses readsparse package in the backend

Bug Fix:

  - CSVSerializer correctly serialize data

                        Changes in version 0.1.0                        

Initial release to r-universe