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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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Hlavní autor: Aggarwal, Charu C. (Autor)
Korporativní autor: SpringerLink (Online service)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Vydání:1st ed. 2024.
Témata:
Machine learning.
Machine Learning.
On-line přístup:https://doi.org/10.1007/978-3-031-53282-5
Tagy: Přidat tag
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Obsah:
  • 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.

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