Practical Data Science With r download free [PDF and Ebook] by Nina Zumel

Practical Data Science With r download free [PDF and Ebook] by Nina Zumel year 2014
  • Book name: Practical Data Science With r
  • Author: Nina Zumel
  • Release date: 2014/3/1
  • Publisher: MANNING PUBLICATIONS
  • Language: English
  • Genre or Collection: Computing
  • ISBN: 9781617291562
  • Rating: 9.17 of 10
  • Votes: 551
  • Review by: Janna Byrd
  • Review rating: 9.18 of 10
  • Review Date: 2018/9/1
  • Total pages: 450
  • Includes a PDF summary of 51 pages
  • Description or summary of the book: DESCRIPTION Simply put, data science is the discipline of extracting meaning from data. While it can involve deep knowledge of statistics, mathematics, machine learning, and computer science, for most non-academics, data science looks like applying analysis techniques to answer key business questions. Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases faced while collecting, curating, and analyzing the data crucial to the success of businesses. Readers will apply the R programming language and statistical analysis techniques to carefully-explained examples based in marketing, business intelligence, and decision support, while learning how to create instrumentation, design experiments such as A/B tests, and accurately present data to audiences of all levels. RETAIL SELLING POINTS Demonstrations of need-to-know statistical ideas Covers all aspects of the project lifecycle Data science for the motivated business professional AUDIENCE Written for the business analyst, technical consultant or technical director- no formal statistics or mathematics background is required. Readers should be comfortable with quantitative thinking plus light scripting or programming. Some familiarity with R is a plus. ABOUT THE TECHNOLOGY R is a programming language which is used for developing statistical software programs. Data Science is the process of collecting data and developing analysis techniques and software over that data to answer key business questions.
  • Estimated reading time (average reader): 22H37M30S
  • Other categories, genre or collection: Software Engineering, Databases, Computer Science, Systems Analysis & Design, Data Mining, Computer Programming / Software Development, Mathematical & Statistical Software, Artificial Intelligence
  • Available formats: OEB, TXT, RB, EPUB, DOC, PDF, LIT, WORD. Compressed in 7Z, RAR, ZIP, GZ
  • Download servers: FreakShare, TusFiles, 4Shared, pyget, Google Drive, BitShare
  • Format: Paperback
  • Approximate value: 41.39 USD
  • Dimensions: 190x235x22mm
  • Weight: 708g
  • Printed by: Not Available
  • Published in: New York, United States
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