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Practical statistics for data scientists : 50+ essential concepts using R and Python
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Tóm tắt
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning
Tác giả
Peter Gedeck
Andrew Bruce
Peter Bruce
Người hướng dẫn
Nơi xuất bản
Nhà xuất bản
O'Reilly Media, Inc.
Năm xuất bản
2020
ISSN tạp chí
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Từ khóa chủ đề
Computer program language , Data processing , Quantitative research , Python