The Data Science Design Manual /

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...

Descrizione completa

Dettagli Bibliografici
Autore principale: Skiena, Steven S.
Ente Autore: SpringerLink (Online service)
Natura: Libro
Lingua:English
Pubblicazione: Cham, Switzerland : Springer, c2017
Serie:Texts in Computer Science,
Soggetti:
Computer science.
Big data.
Data mining.
Pattern recognition.
Mathematics.
Visualization.
Statistics.
Computer Science.
Data Mining and Knowledge Discovery.
Pattern Recognition.
Big Data/Analytics.
Statistics and Computing/Statistics Programs.
Mathematical statistics > Data processing.
Classic Catalogue: View this record in Classic Catalogue
Sommario:
  • 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.

Documenti analoghi