Transition from Civil Engineering to Machine Learning

The chapter explores the journey of the speaker from civil engineering to machine learning, sharing insights into their interest in computer science. It discusses the challenges of applying machine learning models to real-world time series data and categorizes existing forecasting models into statistical local models and task-specific deep learning models. The chapter also delves into leveraging language models for time series forecasting and the tokenization process to convert continuous signals into discrete signals for training language model architectures.