Nonlinear Modeling in R with GAMs

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

GAMs are useful for inference and prediction. GAMs are flexible and more understandable than traditional linear models. GAMs model data relationships using nonlinear functions. This allows them to be used for data science and other data problems. This course will show you how GAMs can be constructed using the popular mgcv software. Learn how to analyse, explain, visualize, and diagnose model problems. GAMs are useful in many different situations. To build mixed linear and nonlinear models, you will need data sets like automobile performance data. Geospatial models can be built using soil pollution data. To classify and predict consumer purchasing data. This course will teach you how to solve data science problems.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems

You'll learn how to interpret, explain and visualize your model results, and how to diagnose and fix model problems

You'll work with data sets that will show you how to apply GAMs to a variety of situations: automobile performance data for building mixed linear and nonlinear models, soil pollution data for building geospatial models, and consumer purchasing data for cl

Course Instructors

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DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of you...

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