Practical Statistics for Data Scientists e-bog
359,43 DKK
(inkl. moms 449,29 DKK)
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,...
E-bog
359,43 DKK
Forlag
O'Reilly Media
Udgivet
10 april 2020
Længde
368 sider
Genrer
Databases
Sprog
English
Format
pdf
Beskyttelse
LCP
ISBN
9781492072911
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 whats important and whats not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If youre 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, youll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "e;learn"e; from dataUnsupervised learning methods for extracting meaning from unlabeled data