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Index
Cover Frontmatter 1. Describing Datasets
1. First Tools for Looking at Data 2. Looking at Relationships
2. Probability
3. Basic Ideas in Probability 4. Random Variables and Expectations 5. Useful Probability Distributions
3. Inference
6. Samples and Populations 7. The Significance of Evidence 8. Experiments 9. Inferring Probability Models from Data
4. Tools
10. Extracting Important Relationships in High Dimensions 11. Learning to Classify 12. Clustering: Models of High Dimensional Data 13. Regression 14. Markov Chains and Hidden Markov Models
5. Mathematical Bits and Pieces
15. Resources and Extras
Backmatter
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