welcome

This book is for data scientist, machine learning engineers and practitioners in the field of forecasting looking to gain cutting-edge knowledge on the latest developments in time series forecasting. As such, we assume the reader is comfortable with basic forecasting concepts, like trend and seasonality, as well as with Python programming.

Also, since we are exploring foundation models, they are inherently deep learning methods, that often rely on the Transformer architecture. Therefore, basic concepts of deep learning like activation functions and feed-forward networks are prerequisites for this book,

In 2023, the field of forecasting still required practitioners to build unique models for each forecasting scenario. In the meantime, the field of natural language processing was seeing an important rise in large language models (LLMs) that were suddenly solving many tasks rapidly and easily.