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Practical Statistics for Data Scientists 50 Essential Conc

Description: 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.

Price: 41 USD

Location: Kalamazoo, Michigan

End Time: 2024-11-05T22:20:19.000Z

Shipping Cost: 6.38 USD

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Practical Statistics for Data Scientists 50 Essential ConcPractical Statistics for Data Scientists 50 Essential ConcPractical Statistics for Data Scientists 50 Essential Conc

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 14 Days

Refund will be given as: Money Back

Number of Pages: 360 Pages

Language: English

Publication Name: Practical Statistics for Data Scientists : 50+ Essential concepts Using Rand Python

Publisher: O'reilly Media, Incorporated

Publication Year: 2020

Subject: Data Processing, Databases / Data Warehousing, Databases / Data Mining, Mathematical Analysis

Item Height: 0.9 in

Item Weight: 22.3 Oz

Type: Textbook

Subject Area: Computers, Mathematics

Author: Peter Bruce, Peter Gedeck, Andrew Bruce

Item Length: 9.2 in

Item Width: 7 in

Format: Trade Paperback

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