Practical Data Science with R pdf epub mobi txt 电子书下载 2025

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Nina Zumel and John Mount are co-founders of Win-Vector, a data science consulting firm in San Francisco. Nina holds a Ph.D. in robotics from Carnegie Mellon and was a content developer for EMC's Data Science and Big Data Analytics Training Course. John has a Ph.D. in computer science from Carnegie Mellon and over 15 years of applied experience in biotech research, online advertising, price optimization and finance. Both contribute to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.

出版者:Manning Publications

作者:Nina Zumel

出品人:

页数:416

译者:

出版时间:2014-4-13

价格:USD 49.99

装帧:Paperback

isbn号码:9781617291562

丛书系列:

图书标签:

R
数据分析
DataScience
数据挖掘
统计学
计算机
数据科学
data

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Simply put, data science is the discipline of extracting meaning from data. More and more business analysts are called to work as data scientists and 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. Sophisticated software and, in particular, the R statistical programming language, gives practical data scientists more tools than ever to help make quantitative business decisions and build custom data analysis tools for business professionals.

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 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-explained examples based in marketing, business intelligence, and decision support. Using these examples, you'll learn how to create instrumentation, to design experiments such as A/B tests, and to accurately present data to audiences of all levels.