1. Create a Model and Save the Model.
A. We have created a simple LinearRegression Model and trained it using Boston Housing Dataset (https://scikit-learn.org/stable/datasets/index.html#boston-house-prices-dataset)
B. Check for accuracy of the model
C. Saved the model as "finalized_model.sav"
Created a python file called “predict.py” to predict value (House Price) based on new input values on the trained model (We hard-coded the new input value for the sake of simplicity)
3. From UiPath using Python Package we called the “Predict.py” to predict prices on-demand
Predicted Output (House Price) value: