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General-purpose ML nodes Domain-specific ML nodes for animation

The example-based ML nodes help to create an ML setup where a model is trained based on labeled examples.

Each labeled example is an input labeled with a desired output (target).

There are two categories of example-based ML nodes: general-purpose ML nodes and domain-specific ML nodes.

The general-purpose ML nodes has a wide variety of cases and are not specific to one application domain. There are domain-specific ML nodes such as the Case study: ML Deformer H20.5 that apply specifically to animation use cases.

General-purpose ML nodes ¶

Data set Processing:

ML Attribute Generate

ML Example

ML Example Decompose

ML Example Partition

ML Extract Example

Training:

ROP ML Example Raw Output

ML Regression Train

Inference:

ML Example Import

ML Regression Inference

ML Regression Proximity

Domain-specific ML nodes for animation ¶

Data set Processing:

ML Pose Generate

ML Pose Serialize

Training:

Inference:

ML Pose Serialize