Diagrams are becoming a prominent tool in both machine learning (ML) and quantum computing. We adapt a key tool of ML, gradients to general diagrammatic theories. This will enable one to do (quantum) ML fully diagrammatically, substantially broadening the road towards general quantum advantage and quantum NLP in particular.

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