Data Science: NLP and Sentimental Analysis in R

supnatural 17 Oct 2021 00:37 LEARNING » e-learning - Tutorial

Data Science: NLP and Sentimental Analysis in R
Data Science: NLP and Sentimental Analysis in R
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 106 lectures (11h 12m) | Size: 4.56 GB

Learn Natural Language Processing and Sentimental Analysis using "The Big Bang Theory" show script in R
What you'll learn:
Use R for Data Science and Machine Learning
Provides the entire toolbox you need to become a NLP engineer
Learn how to pre-process data
Apply your skills to real-life business cases
Able to perform web scraping
Learn text mining
able to perform sentimental analysis on any text

No programming experiences required
No R programming experience required
Machine with any OS (Linux, MacOSX, Windows) and proper internet connection required

Caution before taking this course:

This course does not make you expert in R programming rather it will teach you concepts which will be more than enough to be used in machine learning and natural language processing models.

About the course:

In this practical, hands-on course you'll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.

This course covers following topics:

1. R programming concepts: variables, data structures: vector, matrix, list, data frames/ loops/ functions/ dplyr package/ apply() functions

2. Web scraping: How to scrape titles, link and store to the data structures

3. NLP technologies: Bag of Word model, Term Frequency model, Inverse Document Frequency model

4. Sentimental Analysis: Bing and NRC lexicon

5. Text mining

By the end of the course you'll be in a journey to become Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.

Who this course is for
You should take this course if you want to become a Data Scientist or if you want to learn about the field
You should take this course if you want to learn text mining and text analysis doing fun projects
You should take this course if you want to learn web scraping





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