Information Technology
Hands on Training icon
Hands On Training
Hands on Training icon

Topic Modeling in R

Course Cover

5

(3)

compare button icon
Course Report - Topic Modeling in R

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Course Features

icon

Duration

4 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Mobile, Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

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.

blur
blur

Highlights

blur

Pedagogy

Top 30 Percentile

blur

Rating & Reviews

Top 30 Percentile

blur

Parameters

cv-icon

Pedagogy

Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

cv-icon

Rating & Reviews

This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.

Course Overview

projects-img

Virtual Labs

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

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

Author Image

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%

Course Cover