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Topic Modeling in R

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5

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Course Report - Topic Modeling in R

Course Report

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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

The course introduces students to topics modelling. This course covers topics modeling, including preparation of corpus and fitting topic models with Latent Dirichlet algorithm in package topicmodels. It also includes visualizing results using ggplot2 and wordclouds.

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

Text Mining with Bag-of-Words in R

Introduction to Natural Language Processing in R

What You Will Learn

Learn how to fit topic models using the Latent Dirichlet Allocation algorithm

This course introduces students to the areas involved in topic modeling: preparation of corpus, fitting of topic models using Latent Dirichlet Allocation algorithm (in package topicmodels), and visualizing the results using ggplot2 and wordclouds

Course Instructors

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Pavel Oleinikov

Associate Director, Quantitative Analysis Center, Wesleyan University

Pavel Oleinikov uses his background in social and natural sciences to advance the application of quantitative methods to data from the social world. He teaches courses on basics of Big Data, network ...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

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