Time Series Machine Learning

This book details theories and hands on coding implementation of Machine Learning methods for Time Series. Recent time has seen the surge of deep learning for time series [Wang et al., 2024]. It is important to stay up to date with the latest methods and implementations.

Introduction

• Definitions
• Libraries

Classification

• Overview

Regression

• Overview

Forecasting

• Overview
• Transformer Model

Clustering

• Overview

Hierarchical

• Hierarchical Reconciliation - Australian Tourism Dataset

Anomaly Detection

• Anomaly Detection in Darts
• Anomaly Model: Taxi passengers in NY
• Convert an anomaly score to a binary prediction with a Detector
• A zoom on each anomalies: visualize the results
• Simple case: KMeansScorer

Transfer Learning

• Transfer Learning

Conclusion

• Summary
• References