These example projects demonstrate a full model lifecycle for different versions of a model that were developed in Python and deployed to RStudio Connect using Jupyter Notebooks, Flask, and Plotly Dash.
The data set used in this example involves demographic information and payment history of various customers and whether they defaulted/missed a payment on their credit accounts.
The example projects include:
- Model A - Model Training Notebook [login]
- Model A - REST API Serving Model Predictions [login]
- Model B - Model Training Notebook [login]
- Model B - REST API Serving Model Predictions [login]
- REST API Traffic Router for A/B Testing [login]
- Interactive App to Query and Verify Model Results [login]
RStudio Server Pro can be used with Jupyter Notebooks and machine learning packages to develop, train, and score models during development. RStudio Connect can be used to deploy models and API routers as REST APIs and host published notebooks with details on model training.
The full example is documented at https://solutions.rstudio.com/data-science-admin/model-management/python/.