Notes about the “intro to data science in azure” Learn course:
Autoregressive Integrated Moving Average (ARIMA) model. This is a modeling technique for time series analysis that helps with predictions concerning time.
When you train a model, you need to split your data into training and testing sets so that you don’t train your model on all the data. When using time series data, it’s essential to split the data based on time.
Mean squared error (MSE) is one of the most popular model evaluation metrics in statistical modeling. It allows you to look at how far your predictions are on average from the correct values.