Part 3 – Deep Learning for Time Series

In this part, we focus on the exciting field of deep learning to tackle time series problems. This part starts with a good introduction of the necessary concepts and slowly builds up to different specialized architectures that are suited to handle time series data. It also talks about global models in deep learning and some strategies to make them work better.

This part comprises the following chapters:

• Chapter 11, Introduction to Deep Learning
• Chapter 12, Building Blocks of Deep Learning for Time Series
• Chapter 13, Common Modeling Patterns for Time Series
• Chapter 14, Attention and Transformers for Time Series
• Chapter 15, Strategies for Global Deep Learning Forecasting Models
• Chapter 16, Specialized Deep Learning Architectures for Forecasting