Way to develop graphs and model machine learning
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Graph will have one output and several inputs, a graph is commanded by the output node like a function the node runs by fetching inputs and processing them.
computational graphs can have several purposes but the primal goal was machine learning and have a flow of tensors
Pipeline will have a single input and output and its commanded by the first node when a node is finish it will trigger the next nodes with data generated by the node
Pipelines can also have several purposes but started with the idea of creating some kind of CI where we can graphically see nodes processing, from build to staging
Cache test
UI to create multipurpose flow graphs, upload to the server pass inputs and do training fetch model and use it with new inputs distributed purpose to calculate several nodes across a network
implement common AI methods(funcs) reuse them