Roadmap

[NOTE: this was created in 2017 may and is left here for now just as a historical account. Some of it is still relevant, and some not.]

Development Objectives

The development goals and current work include:

• to expose 100% of Keras functionality to the user
• to create robust synthesis of generality and performance in a single metric
• to use the synthesis score as a metric for optimizing the hyperparameter optimization process
• to leverage gradient based optimization approaches
• to allow on-the-go model ensembling
• to allow ensembling of model ensembles
• to allow reverse inheritance of the optimization capacity i.e. models that build models that...

These goals are currently being met by systematically building simple, easy-to-understand building blocks that solve manageable parts of the challenge.

Immediate Development

• Show false negatives / false positives / border cases
• Robust cross-validation
• Generalization measure
• Prediction task agnostic performance measure
• Adding layer generation for other than Dense layers
• Current custom f1 implementation into Keras metric
• Add support for fastai?