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Index
Cover
Frontmatter
1. Introduction
1. Sensory Data and Features
2. Basics of Sensory Data
3. Handling Noise and Missing Values in Sensory Data
4. Feature Engineering Based on Sensory Data
2. Learning Based on Sensory Data
5. Clustering
6. Mathematical Foundations for Supervised Learning
7. Predictive Modeling without Notion of Time
8. Predictive Modeling with Notion of Time
9. Reinforcement Learning to Provide Feedback and Support
3. Discussion
10. Discussion
Backmatter
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