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Math for Data Science

Math for Data Science presents the mathematical foundations necessary for studying and working in Data Science. The book is suitable for courses in applied mathematics, business analytics, computer science, data science, and engineering. The text covers the portions of linear algebra, calculus, prob...

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Detalles Bibliográficos
Autor principal: Hijab, Omar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edición:1st ed. 2025.
Materias:
Mathematics.
Artificial intelligence > Data processing.
Applications of Mathematics.
Data Science.
Acceso en línea:https://doi.org/10.1007/978-3-031-89707-8
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Tabla de Contenidos:
  • Preface
  • List of Figures
  • Datasets
  • Linear Geometry
  • Principal Components
  • Calculus
  • Probability
  • Statistics
  • Machine Learning
  • A. Auxiliary Material
  • B. Auxiliary Files
  • References
  • Python Index
  • Index.

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