Udemy

Data Science: NLP and Sentimental Analysis in R

立即報名
  • 5,013 名學生
  • 更新於 10/2021
  • 可獲發證書
4.6
(12 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
11 小時 12 分鐘
教學語言
英語
授課導師
Sachin Kafle
證書
  • 可獲發
  • *證書的發放與分配,依課程提供者的政策及安排而定。
評分
4.6
(12 個評分)
2次瀏覽

課程簡介

Data Science: NLP and Sentimental Analysis in R

Learn Natural Language Processing and Sentimental Analysis using "The Big Bang Theory" show script in R.

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.

課程章節

  • 9 個章節
  • 106 堂課
  • 第 1 章 Introduction
  • 第 2 章 Essentials: R programming
  • 第 3 章 IMPORTANT: Data Structures in R
  • 第 4 章 Miscellaneous
  • 第 5 章 Building Logic in R
  • 第 6 章 The "dplyr" package to handle data
  • 第 7 章 Introduction to Text mining
  • 第 8 章 Important Terminologies
  • 第 9 章 Project: Sentimental Analysis with R

課程內容

  • 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


評價

  • J
    Jorico Berongoy
    5.0

    excellent

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