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Supervised Learning in R: Regression

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$12

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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

Regression is a method that uses inputs to predict numerical outcomes. This is machine learning. This course will help you learn about regression models, how to train them in R, and how to make predictions with them.

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

Prerequisites/Requirements

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Introduction to Regression in R

What You Will Learn

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You'll learn about different regression models, how to train these models in R, how to evaluate the models you train and use them to make predictions

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In this chapter we introduce the concept of regression from a machine learning point of view

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While more sophisticated regression techniques manage some of these issues automatically, it's important to be aware of them, in order to understand which methods best handle various issues -- and which issues you must still manage yourself

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Now that we have mastered linear models, we will begin to look at techniques for modeling situations that don't meet the assumptions of linearity

Course Instructors

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John Mount

Co-founder, Principal Consultant at Win-Vector, LLC

John is a co-founder and principal consultant at Win-Vector LLC, a San Francisco data science consultancy. He is the author of several R packages, including the data treatment package vtreat. John is...
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Nina Zumel

Co-founder, Principal Consultant at Win-Vector, LLC

Nina is a co-founder and principal consultant at Win-Vector LLC, a San Francisco data science consultancy. She is co-author of the popular text Practical Data Science with R and occasionally blogs at...

Course Reviews

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Course Cover

$12

$6

49% OFF

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