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An Introduction to Statistical Data Science Theory and Models /

This graduate textbook on the statistical approach to data science describes the basic ideas, scientific principles and common techniques for the extraction of mathematical models from observed data. Aimed at young scientists, and motivated by their scientific prospects, it provides first principle...

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Detalles Bibliográficos
Autor Principal: Picci, Giorgio (Author)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edición:1st ed. 2024.
Subjects:
Statistics .
Machine learning.
Engineering mathematics.
Artificial intelligence > Data processing.
Statistical Theory and Methods.
Bayesian Inference.
Statistical Learning.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Engineering Mathematics.
Data Science.
Acceso en liña:https://doi.org/10.1007/978-3-031-66619-3
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Table of Contents:
  • - 1. Introduction
  • 2. Classical Statistical Inference
  • 3. Linear Models
  • 4. Conditioning and Regularization
  • 5. Linear Hypotheses and LDA
  • 6. Bayesian Statistics
  • 7. Principal Component Analysis
  • 8. Non Linear Inference
  • 9. Time Series.

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