Hands-On Industrial Internet of Things

Building the image of the model

To build the image of the model, we need to write two files: the myenv.yml file, and the core.py file, which contains the code of our model. The myenv.yml file contains the dependencies and can be easily written using the Azure ML service. From the Jupyter Notebook, we can run the following code:

from azureml.core.conda_dependencies import CondaDependenciesmyenv = CondaDependencies()#myenv.add_conda_package("keras")with open("myenv.yml","w") as f:     f.write(myenv.serialize_to_string())

The code of our model should contain two methods: the init() method, and the run() method. In the init() method, the model is loaded and prepared. In our exercise, this simply involves assigning the wind turbine formula to a global ...