With the advent of PyAnsys, which offers Python APIs and modules compatible with Ansys products, there has been a possibility of generating numerically accurate data for any experiments/situations. Considering numerous possibilities for boundary conditions, a strong dataset can be created using PyMAPDL to study structural behavior, that can serve as an input to the ML algorithm for a concerned application. The following lesson discusses the capabilities of PyMAPDL and how does it help to fulfill the basic need of providing synthetic datasets for machine learning algorithms.
1:00 - Definition of AI/ML & NN
1:33 - Pin Code Reader ML Model Example
2:26 - Classification of ML Algorithm
5:30 - Advantages of PyMAPDL for AI/ML
Get more details on PyAnsys here.