Description: Product details Publisher : O'Reilly Media; 2nd edition (June 16, 2020) Language : English Paperback : 360 pages ISBN-10 : 149207294X ISBN-13 : 978-1492072942 Item Weight : 1.3 pounds Dimensions : 7 x 0.9 x 9.1 inchesAbout the book: 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 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 "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data.
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Subject Area: Software Development
Publication Name: Practical Statistics for Data Scientists
Item Length: 9.2in
Publisher: O'reilly Media, Incorporated
Subject: Computer Science
Publication Year: 2020
Type: Textbook
Format: Trade Paperback
Language: English
Item Height: 0.9in
Educational Level: Adult & Further Education
Personalized: No
Author: Peter Bruce, Peter Gedeck, Andrew Bruce
Level: Advanced
Country/Region of Manufacture: United States
Item Width: 7in
Item Weight: 22.3 Oz
Number of Pages: 360 Pages