This course is about making Machine Learning the next tool in your Houdini toolbox. Just like some problems are best solved with vector maths or Vex or Python, some problems get way easier with ML and we want to be able to spot these problems and solve them using your own custom networks.
To do so we create our own training data in Houdini, we build and train our own neural nets with Python and PyTorch and finally integrate them into our Houdini Workflows using ONNX. Additionally we want to take really deep looks into how these setups work and why they’re built the way they are to get a ton of intuition for applying these techniques to new problems.
