Text Mining with R - Complete Hands On From Scratch!

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

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Why to learn Text Mining?

Are you aware that over 2.5 Quintilian bytes of data are created every single day, and it's only going to grow from there. By 2020, it's estimated that 1.7MB of data will be created every second for every person on earth.

Around 90% of world's data is in unstructured format (text data), which makes mining this unstructured data i.e. text mining one of the most sought after skill in Data Science and Machine learning.

  • Who is TEXT MINING SIMPLIFIED course for?
  • Who wants to learn about Text Mining and it's application from scratch?
  • Who wish to learn how to pre-process and analyze textual or social media data, how to read data from different sources, about APIs, etc?
  • Who have some basic idea about R programming (though some basic overview of R programming is covered in this course)?
  • Who are planning to learn most sought after skill in Data Science?
  • Who are planning to take their skills to next level and are planning to learn NLP, after learning text mining skills?
  • Who are beginner in data science but are planning to learn text mining and NLP in near future?

Basic knowledge
  • Should be aware of basic R programming
  • Should have interest in analyzing and deriving insights from social media data i.e. text data
  • Zeal to learn new skills
  • Basic Internet using skills
  • Internet Connectivity

What will you learn
  • Students will learn the text mining concepts and practical approach easily from scratch
  • Students will learn how to analyze and derive insights from their Social Media data
  • Finding out frequently occurring terms from the Twitter data
  • Corpus and it's usage in Text Mining through practical approach
  • Data Mining of text data i.e. unstructured data, in order to derive important insights from social media data
  • Reading files from different sources using R
  • Building a Word Cloud and finding out important insights from it using case study approach
Course Curriculum
Number of Lectures: 16 Total Duration: 01:31:16

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