Simpleml

- Sklearn Pipeline patch
- Changed default log level to INFO

- Thread-safe Keras Sequence dataset splits
- Additional Seq2Seq models
- Bastion tunneling support for SSH db connections
- Explicit modules for constants and imports
- Additional base classes for database connections (plain and alembic)
- Database independent sqlachemy types
- Switched pickle library from dill to cloudpickle
- SQLite support
- Changed default DB connection to SQLite

- Full database initialization with alembic
- DB schema validation on start
- Main configuration file for all credentials
- Drop official support for python 3.4
- Automatic handling of no data operations
- Remaining cloud provider support
- Feature metadata for classification models
- Runtime environment validation
- Add Split and SplitContainer objects
- Simplejson dependency
- Pipeline generator support
- Library specific model base classes
- Generalized database connection classes

- Default identity pipeline
- Alembic integration for database migration
- Standardized model inheritance pattern
- Condensed pandas split dataframes into single df
- Remaining classification metrics
- Updated schema with hash datatype
- Updated hash to use joblib code, consistent across initializations
- Generator pipeline and fitted kwarg
- Dropped base prefixes
- Moved composed subclasses to inits
- Unified datasets and pipelines

- Keras Seq2Seq support
- Keras model support
- Minimized required installation dependencies
- Abstract base classes
- Complex object JSON serialization
- Python 3 compatibility
- Travis and tox for CI/testing

- Save mixins for external files
- Keras sequential model support
- hdf5 binary saving mechanism
- numpy hashing support
- Some tests