Modern Time Series Forecasting with Python

Table of Contents

1. Introducing Time Series
2. Acquiring and Processing Time Series Data
3. Analyzing and Visualizing Time Series Data
4. Setting a Strong Baseline Forecast
5. Time Series Forecasting as Regression
6. Feature Engineering for Time Series Forecasting
7. Target Transformations for Time Series Forecasting
8. Forecasting Time Series with Machine Learning Models
9. Ensembling and Stacking
10. Global Forecasting Models
11. Introduction to Deep Learning
12. Building Blocks of Deep Learning for Time Series
13. Common Modeling Patterns for Time Series
14. Attention and Transformers for Time Series
15. Strategies for Global Deep Learning Forecasting Models
16. Specialized Deep Learning Architectures for Forecasting
17. Probabilistic Forecasting and More
18. Multi-Step Forecasting
19. Evaluating Forecast Errors—A Survey of Forecast Metrics
20. Evaluating Forecasts – Validation Strategies