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Practical data science with R

Practical Data Science with R explains basic principles and then jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully expl...

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Bibliographic Details
Main Author: Zumel, Nina
Other Authors: Mount, John
Format: eBook
Language:English
Published: Shelter Island, NY Manning 2014
Subjects:
Data Mining / Fast
R (langage De Programmation)
Data Mining
Mathematical Statistics / Data Processing / Fast
R (computer Program Language) / Fast
Data Mining / Http://id.loc.gov/authorities/subjects/sh97002073
R (computer Program Language) / Http://id.loc.gov/authorities/subjects/sh2002004407
Mathematical Statistics / Data Processing / Http://id.loc.gov/authorities/subjects/sh85082137
Exploration De Données (informatique)
Statistique Mathématique / Informatique
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Includes bibliographical references and index
  • PART 1 INTRODUCTION TO DATA SCIENCE: The data science process
  • Loading data into R
  • Exploring data
  • Managing data
  • PART 2 MODELING METHODS: Choosing and evaluating models
  • Memorization methods
  • Linear and logistic regression
  • Unsupervised methods
  • Exploring advanced methods
  • PART 3 DELIVERING RESULTS: Documentation and deployment
  • Producing effective presentations

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