Data & Computation
Simulate Scientific Machine Learning
Physics-informed and data-driven models.
▶ Launch the live Scientific Machine Learning simulatorHow to model scientific machine learning in PolySim
- 1
Define the system
Set up the governing equations and parameters for scientific machine learning on the node graph.
- 2
Set boundary & initial conditions
Apply constraints and starting state so the problem is well-posed.
- 3
Choose a solver
Pick an appropriate numerical method and resolution for your accuracy needs.
- 4
Run and inspect
Run locally with WebGPU and explore results in the data inspector.
- 5
Iterate or scale
Adjust parameters live, or scale to the cloud for larger runs.
Scientific Machine Learning is a core topic in data & computation. With PolySim OS you can build a model visually, run it in real time on your own device, and share an interactive version with collaborators or students. Because everything runs in the browser, there is nothing to install and no license to manage — start free and scale only when a problem outgrows your device.
Upgrade your workspace
FEA / Structural Pro Pack — $39
Structural, thermal, and modal finite-element analysis toolset.
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