TensorLab/tensorfx

TensorFX is an end to end application framework to simplifies machine learning with TensorFlow - both training models and using them for prediction. It is designed from the ground up to make the mainline scenarios simple with higher level building blocks, while ensuring custom or complex scenarios remain possible by preserving the flexibility of TensorFlow APIs. Simple, consistent set of usage patterns Local or cloud, single node or distributed execution, in-memory data or big data sharded across files, you should have to write code once, in a single way regardless of how the code executes. A Toolbox with Useful Abstractions The right entrypoint for the task at hand, starting with off-the-shelf algorithms that let you focus on feature engineering and hyperparam tuning. If you need to solve something unqiue, you can focus on building TensorFlow graphs, rather than infrastructure code (distributed cluster setup, checkpointing, logging, exporting models etc.).