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.

Resources¶

• Forecasting: Principles and Practice

• An Introduction to Statistical Learning - with Applications in Python
  [Gareth et al. 2023]