Updated Cookies Notice - you'll see this message only once.

We use cookies and similar technology on this website, which helps us to know a little bit about you and how you use our website. This improves the browsing experience for you and enables us to tailor better products and services to you and others. Cookies are stored locally on your computer or mobile device.
To accept cookies continue browsing as normal or go to the Cookies Notice for more information and to set your preferences.

You have to add this courses into your profile.

Learn By Building Real World Projects

Text Mining and Natural Language Processing in R

Hands-On Text Mining and Natural Language Processing (NLP) Training for Data Science Applications in R

  • |
  •   Lectures: 80
  • |
  •   Videos: 8.5 hours
  • |
  •   Level: All
  • |
  •   Language: English
  • |
  •   Last Updated: 03/2018

  • Instructor : Eduonix Learning Solutions

Check Out Some of Our Other Popular Courses

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you’ll easily use packages like caret, dplyr to work with real data in R. You will also learn to use the common social media mining and natural language processing packages to extract insights from text data.  

I will even introduce you to some very important practical case studies - such as identifying important words in a text and predicting movie sentiments based on textual reviews. You will also extract tweets pertaining to trending topics and analyze their underlying sentiments and identify topics with Latent Dirichlet allocation. With this Powerful course, you’ll know it all: extracting text data from websites, extracting data from social media sites and carrying out analysis of these using visualization, stats, machine learning, and deep learning!  

Start analyzing data for your own projects, whatever your skill level and Impress your potential employers with actual examples of your data science projects.

HERE IS WHAT YOU WILL GET:

  • Data Structures and Reading in R, including CSV, Excel, JSON, HTML data.
  • Web-Scraping using R
  • Extracting text data from Twitter and Facebook using APIs
  • Extract and clean data from the FourSquare app
  • Exploratory data analysis of textual data
  • Common Natural Language Processing techniques such as sentiment analysis and topic modelling
  • Implement machine learning techniques such as clustering, regression and classification on textual data
  • Network analysis

All the data and code used in the course has been made available free of charge and you can use it as you like. You will also have access to additional lectures that are added in the future for FREE.