v1.0

Here is a list of new additions:

• ChemML models can now be saved and loaded (tutorial)
• The tensorflow.keras object can also be extracted from ChemML models for external use (tutorial)
• Transfer learning can now be implemented via the new TransferLearning module using from chemml.models import TransferLearning
• hyperparameter optimization using genetic algorithms can now be performed using the graphical user interface (GUI) as well (tutorial)
• There is a small change in the installation instructions to facilitate the use of the GUI (instructions)

v0.6.0

Here is the list of new additions:

• local atom and bond features for graph convolutional networks
• multiprocessing for local features, coulomb matrix and bag of bonds
• multiobjective genetic algorithm

These are significant additions that pave the way for upcoming descriptors, which support multiprocessing as well >>> deserves incrementing major beta version to v0.6 >>> more is coming in v0.6.x :)

v0.5.4

Fixed access to the static files in the datasets directory.

v0.5.5

• debugged the header issue with bag_of_bonds descriptors.
• build is finally passed and tested on different platforms + added new installation instructions.

v0.5.2

This is the 5th beta release so far.
The 0.4.* versions are written in Python 2 and include chemml wrapper.
The 0.5.0 version is compatible with Python 2 and 3.
The 0.5.1-2 versions are only compatible with Python 3. We decided to phase out the support for Python 2.
The 0.5.2 version provides efficient molecular descriptor implementations that only accept the built-in Molecule object as input.