50+ essential concepts using R and Python/2ND /ED Bruce, Peter Additional Author mixed material bibliography Beijing O\'Reilly Media, Inc., Sebastopol, CA 2020 en English

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xvi, 298 pages : illustrations ; 24 cm 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 popular guide adds comprehensive examples in Python, provides practical guidance on applying 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 science resources incorporate statistical methods but lack a deeper statistical perspective. If you?re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you?ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that "learn" from data Unsupervised learning methods for extracting meaning from unlabeled data Bruce, Peter 1. Computer Science 2. Software Engineering 3. Dat Data Science Information Technology 001.422 9781118881354 NUML LIBRARY RAWALPINDI (National University of Modern Languages) NUML library is the state of art which equipped “RESEARCH FACILITATION CENTRE” with latest computers for readers to access the digital library of more than 23000 research journals and 130000 online books and E-Library of NUML-Rawalpindi. 001.422 BRU 14229 14229.jpg.jpg 21483 2026-02-02 16:13:07 2026-02-03 16:14:24 machine generated