Machine Learning#
The concept of Machine Learning (ML) is a wide umbrella covering many aspects of data analysis and overlaps with statistics.
A basic knowledge of ML is assumed, so for instance prediction models for tabular data is not handled as a separate topic.
To prepare for deployment, we have selected the following main topics:
Pivoting: Data aggregation over categorical variables, e.g., finding average sales per representative in a company.
Forecasting: Using ML or autoregressive models for prediction of future samples.
Including a brief overview of the SARIMAX family of methods.
Streaming and model updates: Tools for partial fits and streaming updates of models.