Rain prediction

Now that we understand machine learning, and we have already worked on IoT, let's work on a simple experiment that shows the value of using ML in IoT.

In this chapter, we are going to perform the following operations:

1. Use historical data to build a data model
2. Get real-time data from a sensor and feed it to the model
3. Based on the inputs to the model, predict the output

Here, we are going to use historical weather data and then build a data model that accepts temperature and humidity values and returns the probability of rain.

We are going to use Azure Machine Learning Studio for this, and we are going to work along the lines of an article named Weather forecast using the sensor data from your IoT hub in Azure Machine Learning at https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-weather-forecast-machine-learning.

We are not going to implement all the...