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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Bibliographic Details
Main Author: Skiena, Steven S. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Series:Texts in Computer Science,
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • 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.