The Data Science Design Manual /

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and...

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Podrobná bibliografie
Hlavní autor: Skiena, Steven S.
Korporativní autor: SpringerLink (Online service)
Médium: Kniha
Jazyk:English
Vydáno: Cham, Switzerland : Springer, c2017
Edice:Texts in Computer Science,
Témata:
Classic Catalogue: View this record in Classic Catalogue
Obsah:
  • What is Data Science?
  • Mathematical Preliminaries
  • Data Munging
  • Scores and Rankings
  • Statistical Analysis
  • Visualizing Data
  • Mathematical Models
  • Linear Algebra
  • Linear and Logistic Regression
  • Distance and Network Methods
  • Machine Learning
  • Big Data: Achieving Scale.