Practical Statistics for Data Scientists: 50 Essential Concepts

Peter Bruce, Andrew Bruce ... 320 pages - Publisher: O'Reilly; (May, 2017) ... Language: English - ISBN-10: 1491952962 - ISBN-13: 978-1491952962. 

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide 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 science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, 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.

Practical Statistics for Data Scientists: 50 Essential Concepts, Peter Bruce, Andrew Bruce

Post a Comment

Hello. GeoTeknikk.COM’s portfolio of engineering resources provides comprehensive coverage across some disciplines: Civil Engineering [Coastal, Waterway & Ocean Engineering - Construction Engineering - Dams & Hydraulic Engineering - Earthquake Engineering - Geotechnical Engineering - Structural Engineering - Transportation Engineering - Engineering Economy and Mathematics] . Computer Engineering [Design and Build WebSites: HTML, JavaScript, CSS, ASP.Net, PHP, ASP - Programming Languages: Fortran, MatLab, Java, Python, Turbo Pascal, Visual Basic, C++] . Geology Engineering ... Environmental Engineering . GeoEnvironmental Engineering . Rock Engineering . Technical Drawing and CAD . English Language [IELTS, Grammar Books, Exercise (Work) Books, Dictionaries] .

Contact Form

Name

Email *

Message *

Theme images by blue_baron. Powered by Blogger.