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This workshop provides an introduction to machine learning and neural networks in DeepPumas. Through a series of examples and exercises, it showcases the DeepPumas functionality and syntax for machine learning and neural networks, and introduces fundamental concepts and Generalization.
Prerequisites
The workshop is targeted to users familiar with statistical modeling and pharmacometrics who want to take advantage of DeepPumas to augment their models with machine learning components. Previous experience in machine learning is helpful but not required. We recommend users being familiar with the Pumas ecosystem and workflows, as covered in the NLME Modeling Workshop and its pre-requisites.
Schedule
| Time (HH:MM) | Activity | Description |
|---|---|---|
| 00:00 | Setup | Download files required for the workshop |
| 00:05 | A simple machine learning model | Work on 1-linear_regression.jl |
| 00:10 | Capturing complex relationships | Work on 2-complex-relationships.jl |
| 00:20 | Bias-variance tradeoff | Work on 3-bias-variance_tradeoff.jl |
| 00:35 | Generalization | Work on 4-generalization.jl |
| 00:50 | Closing remarks | Q&A and feedback |
Get in touch
If you have any suggestions or want to get in touch with our education team, please send an email to training@pumas.ai.
Authors
- Andreu Vall - andreu@pumas.ai
- Niklas Korsbo - niklas@pumas.ai
License
This content is licensed under Creative Commons Attribution-ShareAlike 4.0 International.
