Probability and Statistics for Machine Learning A Textbook
This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories: 1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapte...
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| Format: | eBook |
| Language: | English |
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Cham
Springer Nature Switzerland
2024, 2024
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| Edition: | 1st ed. 2024 |
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| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Chapter. 1. Probability and Statistics: An Introduction
- Chapter. 2. Summarizing and Visualizing Data
- Chapter. 3. Probability Basics and Random Variables
- Chapter. 4. Probability Distributions
- Chapter. 5. Hypothesis Testing and Confidence Intervals
- Chapter. 6. Reconstructing Probability Distributions from Data
- Chapter. 7. Regression
- Chapter. 8. Classification: A Probabilistic View
- Chapter. 9. Unsupervised Learning: A Probabilistic View
- Chapter. 10. Discrete State Markov Processes
- Chapter. 11. Probabilistic Inequalities and Extreme Value Analysis
- Bibliography
- Index