Description: Data Science, Analytics and Machine Learning With R, Paperback by Favero, Luiz; Belfiore, PatrĂcia; Souza, Rafael De Freitas, ISBN 012824271X, ISBN-13 9780128242711, Brand New, Free shipping in the US Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. Th emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. Presents a comprehensive and practical overview of machine learning, data mining and AI techniques for a broad multidisciplinary audience Serves readers who are interested in statistics, analytics and modeling, and those who wish to deepen their knowledge in programming through the use of R Teaches readers how to apply machine learning techniques to a wide range of data and subject areas Presents data in a graphically appealing way, promoting greater information transparency and interactive learning
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Book Title: Data Science, Analytics and Machine Learning With R
Number of Pages: 720 Pages
Publication Name: Data Science, Analytics and Machine Learning with R
Language: English
Publisher: Elsevier Science & Technology
Subject: Intelligence (Ai) & Semantics, Economics / General
Publication Year: 2023
Type: Textbook
Subject Area: Computers, Business & Economics
Author: Patricia Belfiore, Rafael De Freitas Souza, Luiz Paulo Favero
Item Length: 10.9 in
Item Width: 8.5 in
Format: Trade Paperback