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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 20 lectures (3h 43m) | Size: 2.7 GB

In this Course Series, we discuss Practical Applications developed using R. In this part, we discuss Emotion Analysis.

What you'll learn:
Sentiment Analysis
Emotion Analysis
Creating Shiny App
Creating R Markdown
Use of many related R Libraries

Requirements
Knowledge of R Programming Essential
Knowledge of using RStudio Essential
Exposure to Computer Software Programming Essential

Description
In this course series, application developed using R language are discussed. We will cover topics from simple applications like creating Word Clouds to complex applications like Emotion Analysis, Churn Management, Stock Market Prediction, etc. All the applications discussed in the course have been developed through research by me. All the products discussed are being used for different organisational operations in my company and/or by our Customers.

The course start with discussing simple applications through which concepts and applications of supporting tools including R Language features. Tools like knitR, Shiny, etc are discussed. The goal is to develop a concept into an Algorithm and end with developing a Data Product which could be released for consumption in the Market. We will discuss how to publish the Data Products so that it could be available to everyone on the Internet.

Though this course provides a primer on R Programming, it is highly desirable that the Learner has a reasonably good exposure to R Programming. The learner is expected to have installed tools using which R Programming could be conducted. In case, the Learner needs help with getting started with R Programming, they could go through the course "Learning R through an Example".

The course is broken into 3 parts. In each part,1 or more main application is discussed.

In this part, i.e. Part 1, Emotion Analysis is the topic of discussion.

The discussion on Emotion Analysis starts with understanding Sentiment Analysis and then proceeds to Emotion Analysis. The needed concepts of Sentiment Analysis and Emotion Analysis are discussed. The different libraries available in R Language is exposed. The course ends with developing a Data Product for Emotion Analysis.

Who this course is for
Marketing Specialist
Business Development Specialist
Business Intelligence Consultant
Business Analyst
E-Commerce Specialist
Salesperson
HR Specialist
Researcher
Student

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